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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2002

Initial Mechanical Testing of Superalloy Lattice Block Structures Conducted

The first mechanical tests of superalloy lattice block structures produced promising results for this exciting new lightweight material system. The testing was performed in-house at NASA Glenn Research Center's Structural Benchmark Test Facility, where small subelement-sized compression and beam specimens were loaded to observe elastic and plastic behavior, component strength levels, and fatigue resistance for hundreds of thousands of load cycles. Current lattice block construction produces a flat panel composed of thin ligaments arranged in a three-dimensional triangulated trusslike structure. Investment casting of lattice block panels has been developed and greatly expands opportunities for using this unique architecture in today's high-performance structures. In addition, advances made in NASA's Ultra-Efficient Engine Technology Program have extended the lattice block concept to superalloy materials. After a series of casting iterations, the nickel-based superalloy Inconel 718 (IN 718, Inco Alloys International, Inc., Huntington, WV) was successfully cast into lattice block panels; this combination offers light weight combined with high strength, high stiffness, and elevated-temperature durability. For tests to evaluate casting quality and configuration merit, small structural compression and bend test specimens were machined from the 5- by 12- by 0.5-in. panels. Linear elastic finite element analyses were completed for several specimen layouts to predict material stresses and deflections under proposed test conditions. The structural specimens were then subjected to room-temperature static and cyclic loads in Glenn's Life Prediction Branch's material test machine. Surprisingly, the test results exceeded analytical predictions: plastic strains greater than 5 percent were obtained, and fatigue lives did not depreciate relative to the base material. These assets were due to the formation of plastic hinges and the redundancies inherent in lattice block construction, which were not considered in the simplified computer models. The fatigue testing proved the value of redundancies since specimen strength was maintained even after the fracture of one or two ligaments. This ongoing test program is planned to continue through high-temperature testing. Also scheduled for testing are IN 718 lattice block panels with integral face sheets, as well as specimens cast from a higher temperature alloy. The initial testing suggests the value of this technology for large panels under low and moderate pressure loadings and for high-risk, damage-tolerant structures. Potential aeropropulsion uses for lattice blocks include turbine-engine actuated panels, exhaust nozzle flaps, and side panel structures.

Krause, David L.↗
DOE OSTI2018

Sustainable Data Evolution Technology (SDET) for Power Grid Optimization (Final Report)

This project develops an innovative sustainable data evolution technology (SDET) to create open-access power grid datasets and facilitate updates to these datasets by the power grid community. The lack of open-access, realistic large-scale datasets significantly limits the ability of researchers, developers and ultimately end users to develop, benchmark and compare new methods and tools for optimizing the operation and planning of the grid, which leads to slow adoption by end users. Available open datasets include the IEEE sponsored 14-300 bus transmission test cases and distribution test feeders, the Edinburgh Power Systems Test Case Archive (39-2224 buses), and the Polish cases (2383-3375 buses) available with MATPOWER. These datasets serve certain purposes, but for power grid optimization, they are insufficient in one or more of these aspects: 1) they are too small; 2) they are incomplete in both models and scenarios for optimization purposes; and 3) they are static and are not keeping up with grid needs. The SDET technology delivers large-scale realistic datasets and data-creation tools capable of generating new datasets. We work closely with the Category-2 data repository project awarded by the same GRID DATA program. The generated datasets and data creation tools are compatible with and available through the data repository. The objective is to make this a sustained effort within and beyond the ARPA-E GRID DATA program so that the datasets can evolve over time and meet the current and future needs for power grid optimization and potentially other applications in power grid operation and planning. The novel and disruptive features of SDET differentiate itself from prior work in the following aspects: 1) SDET derives features and metrics for both transmission and distribution (T&D) systems by analyzing many public and private datasets provided by our industry partners National Rural Electric Cooperative Association (NRECA) and PJM Interconnection (PJM). 2) SDET develops data-creation tools and use these tools to generate large-scale open-access realistic datasets that comply with the metrics for both T&D systems. 3) SDET validates the created datasets using industry tools provided by our vendor partner GE Energy Solution. The data creation tools, as well as the created datasets, are integrated into the data repository (DR. POWER) funded by ARPA-E GRID DATA program in Category 2. Users can use the datasets and access these data creation tools to create and update datasets, thus datasets can evolve per user requirements and power grid development. The SDET is a novel and disruptive technology compared to current ad hoc and static dataset generation. It is expected the SDET technology will fundamentally enhance the development, assessment, and adoption of new methods and tools for power grid optimization and other applications, which in turn would significantly improve the reliability, resiliency, and efficiency of the power grid – a major ARPA-E mission objective.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Application of Variance Reduction Techniques in RMC Burnup and Thermal-Hydraulic Coupled Calculation

In reactor analog simulation, the Monte Carlo method has relatively high fidelity since it can reduce calculation errors resulting from using approximation methods by describing complex geometry and neutron energy spectra. The Monte Carlo method is, in essence, a stochastic simulation of the neutron transport process, and statistical uncertainty of all the computed results must be provided. In large-scale reactor computation, this method can accurately estimate integral quantities such as the effective multiplication factor (K{sub eff}), and it can limit the uncertainty within an acceptable range via reasonably selecting simulation particles. Nevertheless, it faces great challenges in estimating local quantities like neutron flux and fission power, with uncertainty of estimators beyond acceptance. To decrease the uncertainty of local quantities by increasing simulation particles may cost much time and reduce efficiency. The main reasons are as follows. Firstly, the scale of reactors is so large that common pressurized water reactors have tens of thousands of lattice cells; secondly, uneven distribution of neutron flux and fission power causes uneven distribution of uncertainty. Smith K. puts forward the 95/95 principle to estimate whether uncertainty calculated with Monte Carlo Code satisfies the requirement. According to the principle, with a confidence level of 95%, statistical errors of power density in more than 95% of the regions should be less than 1%. To meet the requirement of the principle, the uniform fission site (UFS) method is raised currently. UFS aims at redistributing fission sources to uniformize the fission source sampling, which can make statistical variance distribution more uniform. This method, which is easy to use, will not obviously increase computation time. Many studies show that UFS has a good variance reduction effect in Monte Carlo criticality calculation, but less attention is paid to its performance in burnup calculation and thermal-hydraulic coupled calculation. Uncertainty arising from the Monte Carlo method has a large impact on burnup calculation and thermal-hydraulic coupled calculation. Variance propagates between burnup steps and between iterative steps of coupled calculation, which causes asymmetry of results of the physical symmetrical regions and instability of coupled iterative convergence errors. To further verify the effect of UFS, this study uses it in the RMC (the Reactor Monte Carlo code) burnup calculation module and the neutronics/thermohydraulics coupled calculation module, and conducts two-dimensional pressurized water reactor burnup calculation and BEAVRS benchmark thermalhydraulic coupled calculation. In this way, it verifies the improvement effect of UFS on variance propagation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1997

Application of PML Absorbing Boundary Conditions to the Benchmark Problems of Computational Aeroacoustics

Accurate numerical non-reflecting boundary conditions are important in all the proposed benchmark problems of the Second Workshop. Recently, a new absorbing boundary condition has been developed using Perfectly Matched Layer (PML) equations for the Euler equations. In this approach, a region with a width of a few grid points is introduced adjacent to the non-reflecting boundaries. In the added region, Perfectly Matched Layer equations are constructed and applied so that the out-going waves are absorbed inside the layer with little reflection to the interior domain. It will be demonstrated in the present paper that the proposed absorbing boundary condition is quite general and versatile, applicable to radiation boundaries as well as inflow and outflow boundaries. It is also easy to implement. The emphasis of the paper will be on the application of the PML absorbing boundary condition to problems in Categories 1, 2, and 3. In Category 1, solutions of problems 1 and 2 are presented. Both problems are solved using a multi-domain polar grid system. Perfectly Matched Layer equations for a circular boundary are constructed and their effectiveness assessed. In Category 2, solutions of problem 2 are presented. Here, in addition to the radiation boundary conditions at the far field in the axisymmetric coordinate system, the inflow boundary condition at the duct inlet is also dealt with using the proposed Perfectly Match Layer equations. At the inlet, a PML domain is introduced in which the incident duct mode is simulated while the waves reflected from the open end of the duct are absorbed at the same time. In Category 3, solutions of all three problems are presented. Again, the PML absorbing boundary condition is used at the inflow boundary so that the incoming vorticity wave is simulated while the outgoing acoustic waves are absorbed with very little numerical reflection. All the problems are solved using central difference schemes for spatial discretizations and the optimized Low-Dissipation and Low-Dispersion Runge-Kutta scheme for the time integration. Issues of numerical accuracy and efficiency are also addressed.

Hu, Fang Q.↗
DOE OSTI2024

EPR studies of ferredoxin in spinach and cyanobacterial thylakoids related to photosystem I-driven NADP + reduction

Photosynthetic light-dependent reactions occur in thylakoid membranes where embedded proteins capture light energy and convert it to chemical energy in the form of ATP and NADPH for use in carbon fixation. One of these integral membrane proteins is Photosystem I (PSI). PSI catalyzes light-driven transmembrane electron transfer from plastocyanin (Pc) to oxidized ferredoxin (Fd). Electrons from reduced Fd are used by the enzyme ferredoxin-NADP + reductase (FNR) for the reduction of NADP + to NADPH. Fd and Pc are both small soluble proteins whereas the larger FNR enzyme is associated with the membrane. To investigate electron shuttling between these diffusible and embedded proteins, thylakoid photoreduction of NADP + was studied. As isolated, both spinach and cyanobacterial thylakoids generate NADPH upon illumination without extraneous addition of Fd. These findings indicate that isolated thylakoids either (i) retain a “pool” of Fd which diffuses between PSI and membrane bound FNR or (ii) that a fraction of PSI is associated with Fd, with the membrane environment facilitating PSI-Fd-FNR interactions which enable multiple turnovers of the complex with a single Fd. To explore the functional association of Fd with PSI in thylakoids, electron paramagnetic resonance (EPR) spectroscopic methodologies were developed to distinguish the signals for the reduced Fe-S clusters of PSI and Fd. Temperature-dependent EPR studies show that the EPR signals of the terminal [4Fe-4S] cluster of PSI can be distinguished from the [2Fe-2S] cluster of Fd at > 30 K. At 50 K, the cw X-band EPR spectra of cyanobacterial and spinach thylakoids reduced with dithionite exhibit EPR signals of a [2Fe-2S] cluster with g-values g x = 2.05, g y = 1.96, and g z = 1.89, confirming that Fd is present in thylakoid preparations capable of NADP + photoreduction. Quantitation of the EPR signals of P 700 + and dithionite reduced Fd reveal that Fd is present at a ratio of ~ 1 Fd per PSI monomer in both spinach and cyanobacterial thylakoids. Light-driven electron transfer from PSI to Fd in thylakoids confirms Fd is functionally associated (< 0.4 Fd/PSI) with the acceptor end of PSI in isolated cyanobacterial thylakoids. Furthermore, these EPR experiments provide a benchmark for future spectroscopic characterization of Fd interactions involved in multistep relay of electrons following PSI charge separation in the context of photosynthetic thylakoid microenvironments.

Electron paramagnetic resonance↗
DOE OSTI2022

Estimation of pipe failure frequencies in the absence of operational experience data: A pilot study

Probabilistic failure metrics such as leak frequency and rupture frequency are commonly used to characterize piping reliability. The methodologies for calculating the failure metrics rely on a complex set of input parameters. Operating experience data and experimental data play an important role in informing the different input parameters. The paper describes results and conclusions of a coordinated research project to benchmark three different reliability models using a four-step procedure: reference case definition of relevance to advanced reactor designs, input parameter calibration, validation of results, and application of different methodologies upon completion of the calibration and validation steps. The reference case is a weld consisting of nickel-base alloy 152/52 and located within a primary pressure boundary of an advanced reactor. This alloy is a class of structural materials known to be highly resistant to stress corrosion cracking. Synergies between the different methods are noted and the importance of a multi-disciplinary approach to input parameter development is underscored. A key conclusion is that the three methods are equally suitable for estimating failure frequencies. In any specific application, a selection of the most practical or effective computational tool can be considered. The comparison of alternative models confirms and helps to gain confidence in the computed failure frequency estimates. The study was part of a coordinated research project organized by the International Atomic Energy Agency.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

A sharp interface Lagrangian-Eulerian method for flexible-body fluid-structure interaction

This paper introduces a sharp-interface approach to simulating fluid-structure interaction (FSI) involving flexible bodies described by general nonlinear material models and across a broad range of mass density ratios. This new flexible-body immersed Lagrangian-Eulerian (ILE) scheme extends our prior work on integrating partitioned and immersed approaches to rigid-body FSI. Our numerical approach incorporates the geometrical and domain solution flexibility of the immersed boundary (IB) method with an accuracy comparable to body-fitted approaches that sharply resolve flows and stresses up to the fluid-structure interface. Unlike many IB methods, our ILE formulation uses distinct momentum equations for the fluid and solid subregions with a Dirichlet-Neumann coupling strategy that connects fluid and solid subproblems through simple interface conditions. As in earlier work, we use approximate Lagrange multiplier forces to treat the kinematic interface conditions along the fluid-structure interface. This penalty approach simplifies the linear solvers needed by our formulation by introducing two representations of the fluid-structure interface, one that moves with the fluid and another that moves with the structure, that are connected by stiff springs. This approach also enables the use of multi-rate time stepping, which allows us to use different time step sizes for the fluid and structure subproblems. Our fluid solver relies on an immersed interface method (IIM) for discrete surfaces to impose stress jump conditions along complex interfaces while enabling the use of fast structured-grid solvers for the incompressible Navier-Stokes equations. The dynamics of the volumetric structural mesh are determined using a standard finite element approach to large-deformation nonlinear elasticity via a nearly incompressible solid mechanics formulation. This formulation also readily accommodates compressible structures with a constant total volume, and it can handle fully compressible solid structures for cases in which at least part of the solid boundary does not contact the incompressible fluid. Selected grid convergence studies demonstrate second-order convergence in volume conservation and in the pointwise discrepancies between corresponding positions of the two interface representations as well as between first and second-order convergence in the structural displacements. The time stepping scheme is also demonstrated to yield second-order convergence. To assess and validate the robustness and accuracy of the new algorithm, comparisons are made with computational and experimental FSI benchmarks. Test cases include both smooth and sharp geometries in various flow conditions. Furthermore, we also demonstrate the capabilities of this methodology by applying it to model the transport and capture of a geometrically realistic, deformable blood clot in an inferior vena cava filter.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Developing And Scaling an OpenFOAM Model to Study Turbulent Flow in a HFIR Coolant Channel

Improving the understanding of how computational fluid dynamics (CFD) direct numerical simulations (DNS) of flows in the High Flux Isotope Reactor (HFIR) perform when run in parallel using the high performance computing (HPC) platform Summit at the Oak Ridge Leadership Computing Facility (OLCF) is of particular importance to boost the computational tools used to support HFIR conversion to low enriched fuel (LEU). Evaluation of scaling performance was driven by the increasing importance of graphics processing unit (GPU) usage in HPC, which is becoming the standard for modern supercomputers such as Summit. The desired results are to obtain a strong positive correlation between the computational resources dedicated to a problem and the relative speed-up of the simulation in comparison to a benchmark. This capability will allow substantially improvement in HFIR flow analytical capabilities, specifically when predicting turbulence properties at high Reynolds numbers. The study leverages previous simulation results performed with code PHASTA (finite element) on HPC platforms Cori (NERSC) and Theta (ALCF) [1] with computing options provided in the computing platform OpenFOAM (finite volume) at OLCF. Transitioning from PHASTA to OpenFOAM will (1) eliminate dependence on third-party software for mesh generation and manipulation, (2) reduce resource needs by employing modern architectures, and (3) build expertise for future modeling of HFIR-specific problems like heat transfer in involute geometry, entrance effects, flow structure in channel corners, and so on—all important issues when defining the available thermal margins in the transition to LEU. CPUs and GPUs differ significantly in their architecture and utilization, as discussed in the literature [2]. The most important differences are in the approach to computations and their memory. A single GPU contains a large quantity of cores, enabling it to perform with a much higher throughput than a CPU, but execution requires a different approach. GPU codes execute instructions using the Single-Instruction Multiple-Thread (SIMT) approach in which a single instruction is used for groups of threads called warps. A warp typically consists of 32 threads which must execute the same set of instructions, although on separate threads. Alternately, a CPU has far fewer cores that are much more flexible in their operation, excelling at quickly performing more complex serial computations. This is why GPUs have greater throughput when properly utilized. The second important difference is seen when comparing their memory spaces. Limited memory allocations and CPU–GPU communications cause a significant bottleneck in GPU-accelerated programs. Further study was required to properly take advantage of GPU resources. A comprehensive analysis of code performance and the model-specific features of turbulence constitutes the core of this work. In this study, a DNS simulation of HFIR channel turbulence was performed with the finite volume CFD code OpenFOAM v2112 and CUDA v11.0 on Red Hat Enterprise Linux v8.2. The OpenFOAM installation had AMGx integrated to enable GPU acceleration and utilizes the PETSc4FOAM library. The computational resources and the problem size were scaled on CPU and CPU + GPU architectures to gain a better understanding of the performance of a DNS problem on modern computing hardware. The study aimed to analyze the scaling of the code exclusively on CPUs and then to examine the scaling of the codes with GPU acceleration enabled. Scaling studies included CPU and GPU acceleration on a mesh of varying resolution to analyze the impact of problem size relative to computational resources. In the course of preparing the GPU configuration on Summit, mainly using the AMGX solvers, difficulties were encountered stemming from constant changes resulting from extensive ongoing development activities and the changing environment. This resulted in the inability to complete the GPU portion of the work. The code was compiled and tested, but production runs to assess acceleration were not performed because the used discretional compute time allocation expired as year-end approached. The Summit HPC platform is scheduled for decommissioning in 2024, making it unattractive for future use with Nvidia-based GPUs. Therefore, the work will be moved onto NERSC machines in FY24. An application was prepared and submitted, and sufficient node-hours were awarded to continue the research in the next calendar year. This report summarizes work performed thus far, which mostly focused on CPU OpenFOAM computing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRSDate not supplied

rHealth One Demonstration Aboard ISS: A Microfluidic Bioanalyzer Based on Sheath/Hydrodynamic Focusing Flow Cytometry

The Exploration Medical Capability (ExMC) element aims to provide astronauts with the means for their own health monitoring, diagnosis, and treatment during exploration missions. As space flight ventures further from earth, the need for autonomous medical care increases under greater constraints on size, mass, and resources. One pillar for diagnosis that crew would be separated from is laboratory analysis. Even now on ISS, blood samples must be collected and returned to earth for testing. In response, ExMC is assessing how assays for hematology, bone health, radiation exposure etc. could be addressed through commercial-off-the-shelf (COTS) and Small Business Innovation Research (SBIR) funded bioanalyzers that are miniaturizing lab technology. Since missions will reach distances where there are no timely replacements, validation on the International Space Station (ISS) is a necessary part of that assessment. In partnership with NASA Johnson Space Center (JSC) Immunology Lab and the Research Operations and Integration (ROI) element, ExMC conducted a technology demonstration on ISS of the rHEALTH ONE, a flow cytometry based bioanalyzer, to assess future devices based on this design. In flow cytometry, there are predominantly three ways to focus the cells (or particles) into a single file stream: hydrodynamic focusing, microcapillary, and acoustic focusing. The rHEALTH ONE utilizes the commercial standard, sheath-based hydrodynamic focusing. rHEALTH itself represents both a company and a suite of medical tools NASA has funded through SBIR grants towards the development of a promising diagnosis instrument for exploration missions. rHEALTH ONE is the interim version of the technology, functional as a benchtop analyzer and test bed for the next generation of rHEALTH in development. Several modifications were made to the rHEALTH ONE analyzer for operation in microgravity. For function, fluid management was key. A sheath-based analyzer uses sheath fluid to flow the sample, cleaning fluid to prevent biological contamination, and a reservoir to collect the liquid waste. The rHEALTH ONE analyzer uses bottles dependent on gravity to separate the air and liquid pathways and keep the liquids contained. It uses only 1 psig of air pressure to directly push the liquid through the device, requiring little-to-no resistance at inlet and outlet. A microtubing assembly with self-sealing luer connectors was designed – featuring 0.014 mm thick durable medical balloons to hold water inside the supply bottles – to create safe containment and easy access for the crew while maintaining the analyzer’s function. For safety, copper tape was added to the interior of the plastic housing to reduce electromagnetic interference, fluid and electrical connections were secured against vibration and leaks, and gaps were further sealed to ensure containment of the optical block and lasers. Water as the sheath and cleaning fluid and TOX 0 samples were used to reduce the biohazard risk to the crew. In May 2022, European Space Agency astronaut Samantha Cristoforetti demonstrated the rHEALTH ONE aboard ISS for its sample loading, flow cytometry, and data collection capability in microgravity. The JSC Immunology Lab provided flow cytometry expertise, designed the sample test protocol, and manufactured and benchmarked the flight samples on a ‘gold-standard’ flow cytometer. The analyzer was primed with water, purged of air, and four calibration solutions of polystyrene microparticles were tested to characterize its performance. Tightly controlled procedures and excellent execution prevented air bubble interference during air/water separation, fluid transfer, sample mixing and loading. Data showed a slight increase in signal noise on 3 of 5 channels and an anomaly of fluorophores migrating in one sample (confirmed by JSC post-flight). Flight results correctly detected the change in sample, matched the analyzer’s ground performance, and were consistent with the gold-standard’s ground results. Although areas were noted for improvement, these outcomes signified complete mission success.

R. S. Miller↗
NASA NTRSDate not supplied

ANALYSIS OF THE MSL/MEDLI ENTRY DATA WITH COUPLED CFD AND MATERIAL RESPONSE.

The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heat-shield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material. PICA is a lightweight carbon fiber/polymeric resin material that offers out-standing performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on Open-FOAM (PATO) using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA, is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.

Mars Science Laboratory↗
DOE OSTI2022

Neutron Leakage Spectra Sensitivities for ICSBEP Benchmarks

Neutron leakage spectra have been measured, simulated, and investigated by many groups. These spectra have many uses, including determining shielding requirements and calculating dose for radiation protection purposes, validating nuclear data, and determining material composition. It has even been proposed to use measurements of neutron leakage spectra to determine the soil composition of Mars. As part of the Los Alamos National Laboratory (LANL) Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) Laboratory Directed Research Development (LDRD) project, the authors are working on developing methods to calculate sensitivities to neutron leakage spectra. This may allow nuclear data evaluators to better use neutron leakage spectra data to constrain or adjust nuclear data. This may also be particularly useful as many neutron leakage spectra measurements do not require fissile material and can be performed with well characterized neutron sources. Neutron leakage spectra measurements are usually performed by placing a detector at the outside of a nuclear system. This may be a reactor, a neutron generator, or a neutron source. Certain detection systems can use pulse height data to infer neutron energies, other detector systems rely on other ways of determining neutron energy (for example, a Bonner sphere with multiple moderator thicknesses can be used to measure neutron spectrum). These measurements typically rely on some unfolding of the measured results. For pulsed systems like the "Livermore Pulsed Spheres," time-of-flight information can also help to constrain the neutron energy spectra data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

Analysis of MSL/MEDLI Entry Data with Coupled CFD and Material Response

The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heatshield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material [1]. PICA is a lightweight carbon fiber/polymeric resin material that offers outstanding performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP) [2]. The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on OpenFOAM (PATO) [4,5,6] using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA [7], is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.

Thermal Protection Systems↗
DOE OSTI2020

Methods and Experiences for Developing Abstractions for Data-intensive, Scientific Applications

Developing software for scientific applications that require the integration of diverse types of computing, instruments, and data present challenges that are distinct from commercial software. These applications require scale, and the need to integrate various programming and computational models with evolving and heterogeneous infrastructure. Pervasive and effective abstractions for distributed infrastructures are thus critical; however, the process of developing abstractions for scientific applications and infrastructures is not well understood. While theory-based approaches for system development are suited for well-defined, closed environments, they have severe limitations for designing abstractions for scientific systems and applications. The design science research (DSR) method provides the basis for designing practical systems that can handle real-world complexities at all levels. In contrast to theory-centric approaches, DSR emphasizes both practical relevance and knowledge creation by building and rigorously evaluating all artifacts. In this work, we show how DSR provides a well-defined framework for developing abstractions and middleware systems for distributed systems. Specifically, we address the critical problem of distributed resource management on heterogeneous infrastructure over a dynamic range of scales, a challenge that currently limits many scientific applications. We use the pilot-abstraction, a widely used resource management abstraction for high-performance, high throughput, big data, and streaming applications, as a case study for evaluating the DSR activities. For this purpose, we analyze the research process and artifacts produced during the design and evaluation of the pilot-abstraction. We find DSR provides a concise framework for iteratively designing and evaluating systems. Finally, we capture our experiences and formulate different lessons learned.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Co-optimization of CO 2 -EOR and Storage Processes under Geological Uncertainty

This paper presents an integrated numerical framework to co-optimize EOR and CO 2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. The framework includes a field-scale compositional reservoir flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. A laboratory fluid analysis was tuned to an equation of state and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). A history match of primary and secondary recovery processes was conducted to estimate the reservoir and multiphase flow parameters as the baseline case for analyzing the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO 2 storage. A multi-objective optimization model was defined for maximizing both oil recovery and CO 2 storage. The uncertainty quantification model comprising the Latin Hypercube sampling, Monte Carlo simulation, and sensitivity analysis, was used to study the effects of uncertain variables on the defined objective functions. Uncertain variables such as bottom hole injection pressure, WAG cycle, injection and production group rates, and gas-oil ratio among others were selected. The most significant variables were selected as control variables to be used for the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without geological uncertainty. The vertical permeability anisotropy (Kv/Kh) was selected as one of the uncertain parameters in the optimization process. The simulation results were compared to a scenario baseline case that predicted CO 2 storage of 74%. The results showed an improved approach for optimizing oil recovery and CO 2 storage in the FWU. The optimization process predicted more than 94% of CO 2 storage and most importantly about 28% of incremental oil recovery. The sensitivity analysis reduced the number of control variables to decrease computational time. A risk aversion factor was used to represent results at various confidence levels to assist management in the decision-making process. The defined objective functions were proved to be a robust approach to co-optimize oil recovery and CO 2 storage. The Farnsworth CO 2 project will serve as a benchmark for future CO 2 –EOR or CCUS projects in the Anadarko basin or geologically similar basins throughout the world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Progress on Optimizing Wind Farms and Rotor Designs Using Adjoints

Modern wind plants are increasingly tasked with multiple performance objectives. In addition to designing plants that maximize power output and minimize the levelized cost of energy (LCOE), the design and operation of wind plants is increasingly influenced by challenges regarding grid integration of variable generation renewables. This places a growing emphasis on making wind plants more controllable and predictable. WindSE is a Reynolds-averaged Navier-Stokes (RANS) model designed around analytical gradient and adjoint methods, with the ability to capture terrain-induced effects, as shown in Figure 1. The recent addition of an unsteady solver with an actuator line method (ALM) and ongoing work to enable massively parallel optimizations gives it a unique niche to explore coupled plant-level controls and design problems. This code is an open source python package built on the FEniCS framework that utilizes fast, parallel PETSc solvers to model fluid flow throughout wind-farm scale domains. Two recent studies performed using WindSE demonstrate the capability to optimize under a wide variety of flow conditions and objective functions. In the first, we present an optimization focused on modifying the layout of a wind farm with a fixed number of turbines for maximum total power output [1]. This study highlights the ability to quickly perform simulations using the steady Navier-Stokes solver combined with rotors represented as actuator disks while also stressing the importance of capturing terrain-induced effects. Gradient-based optimization using the RANS equations is viable due to the inclusion of efficiently computed adjoint derivatives. We interpret the physical results of the optimal layout and also discuss the computational cost of scaling to larger problems. In the second study, we present the capabilities of the unsteady Navier-Stokes solver, where rotor-blade profiles represented by actuator lines are optimized to enhance wake steering effects and overall power production [2]. We quantify the wind plant performance gains obtained from this type of simultaneous control co-design optimization as compared to optimizing the blade design and yaw independently. Figure 2 shows the differences between a baseline two-turbine system and an optimized system where we fine-tune the blade chord profile. Results and challenges from each study are quickly summarized and used to motivate the current development efforts within WindSE. Current and future work is focused on enabling higher-resolution studies with more degrees of freedom through parallelization of both the simulation and optimization algorithms. We present benchmarking results to show that WindSE performs well in both weak- and strong-scaling tests and further demonstrate that the optimizer obtains the same convergence rates in both shared- and distributed-memory environments. Using larger wind farms, we can study deep-array effects within an optimization context, allowing the use of objective functions that have been previously unstudied. As an example, we present ongoing work on a blockage metric which characterizes the loss of available kinetic energy due to wake effects from multiple upstream turbines.

adjoint optimization↗
NASA NTRS2013

Engineering Evaluation of International Low Impact Docking System Latch Hooks

The international Low Impact Docking System (iLIDS) provides a structural arrangement that allows for visiting vehicles to dock with the International Space Station (ISS) (Fig 1). The iLIDS docking units are mechanically joined together by a series of active and passive latch hooks. In order to preserve docking capability at the existing Russian docking interfaces, the iLIDS latch hooks are required to conform to the existing Russian design. The latch hooks are classified as being fail-safe. Since the latch hooks are fail-safe, the hooks are not fracture critical and a fatigue based service life assessment will satisfy the structural integrity requirements. Constant amplitude fatigue testing to failure on four sets of active/passive iLIDS latch hooks was performed at load magnitudes of 10, 11, and 12 kips. Failure analysis of the hook fatigue failures identified multi-site fatigue initiation that was effectively centered about the hook mid-plane (consistent with the 3D model results). The fatigue crack initiation distribution implies that the fatigue damage accumulation effectively results in a very low aspect ratio surface crack (which can be simulated as thru-thickness crack). Fatigue damage progression resulted in numerous close proximity fatigue crack initiation sites. It was not possible to determine if fatigue crack coalescence occurs during cyclic loading or as result of the fast fracture response. The presence of multiple fatigue crack initiation sites on different planes will result in the formation of ratchet marks as the cracks coalesce. Once the stable fatigue crack becomes unstable and the fast fracture advances across the remaining ligament and the plane stress condition at a free-surface will result in failure along a 45 deg. shear plane (slant fracture) and the resulting inclined edge is called a shear lip. The hook thickness on the plane of fatigue crack initiation is 0.787". The distance between the shear lips on this plane was on the order of 0.48" and it was effectively centered about the mid-plane of the section. The numerous ratchet marks between the shear lips on the fracture initiation plane are indicative of multiple fatigue initiation sites within this region. The distribution of the fatigue damage about the centerline of the hook is consistent with the analytical results that demonstrate peak stress/strain response at the mid-plane that decreases in the direction of the hook outer surfaces. Scanning electron microscope images of the failed sections detected fatigue crack striations in close proximity to the free surface of the hook radius. These findings were documented at three locations on the fracture surface : 1) adjacent to the left shear lip, 2) adjacent to the right shear lip, and 3) near the centerline of the section. The features of the titanium fracture surface did not allow for a determination of a critical crack size via identification of the region where the fatigue crack propagation became unstable. The fracture based service life projections where benchmarked with strain-life analyses. The strainrange response in the hook radius was defined via the correlated finite element models and the modified method of universal slopes was incorporated to define the strain-life equation for the titanium alloy. The strain-life assessment confirmed that the fracture based projections were reasonable for the loading range of interest. Based upon the analysis and component level fatigue test data a preliminary service life capability for the iLIDS active and passive hooks of 2 lifetimes is projected (includes a scatter factor of 4).

Martinez, J.↗
DOE OSTI2021

Preliminary RAM-RODD results for the MUSiC subcritical configurations

The Measurement of Uranium Subcritical and Critical (MUSiC) was performed at the DOE’s National Criticality Experiments Research Center (NCERC) located in the Nevada National Security Site (NNSS). The measurement utilized the Rocky Flats shells to perform benchmark measurements of similar highly enriched uranium (HEU) systems that span a wide range of reactivities. The Rocky Flats (RF) shells are 93.16% U-235 enriched metal hemishells that can be stacked concentrically. Ten configurations were measured with effective multiplication factors spanning between deeply subcritical (~ 0.64) through delayed critical. Details of the measured configurations are listed in Table 1. This unique set of measurements with its large span of reactivies is being used to determine the range over which neutron noise techniques such as Feynman variance-to-mean, Rossi-alpha, and pulsed neutron source techniques can be accurately employed for a bare HEU system. The results of the measurements will be published as a benchmark in The International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The results will support the growing amount of subcritical benchmark data, such as the SCRaP measurements, that is available to the community. The measurements were performed using several different detector systems for the purposes of cross-validation and obtaining detector independent results. Four detector systems were deployed, three by the NCERC team and one from the University of Michigan. The detector systems included a Neutron Multiplicity Array Detector (NoMAD) system (similar to the MC-15), four small volume 0.635 cm (Ø) × 7.59 cm 3 He detectors (ideal for measuring prompt neutron decay constants due to their fast recovery speed), the Rossi Alpha Measurements – Rapid Organic (n, γ) Discrimination Detector (RAM-RODD), and the Organic Scintillator Array (OSCAR). RAM-RODD is an array of eight 5.08 cm (Ø) × 5.08 cm EJ-309 organic scintillator detectors. OSCAR is a University of Michigan system and is an array of twelve 5.08 cm (Ø) × 5.08 cm stilbene detectors. Details of measurements performed with OSCAR will be discussed in a separate talk. The focus of this work is preliminary results obtained by RAM-RODD for the 8 subcritical configurations. Additional details on the measurements and on the setup and deployment of RAM-RODD will be discussed. Preliminary neutron noise analysis results including Rossi-alpha and Feynman-alpha will also be presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Hydrogen Production System Scaling Using a High-Fidelity Simulation-Optimization Framework

Proton exchange membrane (PEM) electrolyzers are widely used for hydrogen production, yet few validated, high-fidelity tools can reliably guide scale-up. Using measured performance from a 50-hour hardware-in-the-loop pilot test, a physics-based, plant-level model of a 1.25 MW PEM electrolyzer and its balance-of-plant (BoP) subsystems is developed and validated. The model couples electrochemistry and thermal/flow submodels and is calibrated against pilot test data via a genetic algorithm (GA) workflow. Validation yields a mean absolute percentage error (APE) of 0.43% for cell voltage and stack power. Two scale-out strategies are then benchmarked under a common 7-day wind-and-photovoltaic (PV) profile: (i) linear duplication of 1.25 MW blocks and (ii) shared-BoP architectures. Sharing BoP between stacks reduces BoP energy by 27% at 10 MW and 34% at 100 MW (vs. linear duplication) and improves system specific energy consumption (SEC) to 52.9 and 52.6 kWh/kg, respectively (from 54.0 kWh/kg with linear duplication). Partial-load studies (25-100% set-point) show that cumulative hydrogen production remains nearly constant down to 50% load because all cases use the same weekly renewable-energy input. Below 50%, the power cap limits how much energy can be used within 168 h, which reduces hydrogen output. The model further indicates that the practical operating optimum lies between 50% and 85% load, where efficiency gains begin to appear without significant loss in hydrogen output. Moreover, the efficiency gains at lower loads are offset by reduced production. The validated framework supports scenario-based engineering trade-off studies for large configurations (10-100 MW) and for operating policies under variable renewables.

08 HYDROGEN↗

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