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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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At least 469 records · Page 26

Operational design factors for NASP derived vehicles

The factors that significantly affect the operability of aerospace planes are identified and considered in terms of the development of the National Aerospace Plane (NASP). The aircraftlike vehicle can be affected by variables related to the structure, propulsion, and mechanical elements of the design. The requirements to control the factors are listed including robustness, fuels and propellants, maintainability, autonomy, and development testing. The details of the requirements indicate critical factors such as the strength-to-weight ratios of the materials, propellant-system components that can withstand 5000 consecutive cycles, and low vehicle-failure probabilities. The NASP program is concluded to require: (1) models for quantitative operational assessments; (2) a modular design for the NASP structure; (3) computer-technology integration; and (4) technologies to support and normalize cryogenic operations.

Hickman, R. A.↗

Program Simulates A Modular Manufacturing System

SSE computer program provides simulation environment for modeling manufacturing systems containing relatively small numbers of stations and operators. Designed to simulate manufacturing of apparel, also used in other manufacturing domains. Excellent for small or medium-size firms including those lacking expertise to develop detailed models or have only minimal knowledge in describing manufacturing systems and in analyzing results of simulations on mathematical models. User does not need to know simulation language to use SSE. Used to design new modules and to evaluate existing modules. Originally written in Turbo C v2.0 for IBM PC-compatible computers running MS-DOS and successfully implemented by use of Turbo C++ v3.0.

Schroer, Bernard J.↗

Another Program Simulates A Modular Manufacturing System

SSE5 computer program provides simulation environment for modeling manufacturing systems containing relatively small numbers of stations and operators. Designed to simulate manufacturing of apparel, also used in other manufacturing domains. Valuable for small or medium-size firms, including those lacking expertise to develop detailed mathematical models or have only minimal knowledge in describing manufacturing systems and in analyzing results of simulations on mathematical models. Two other programs available bundled together as SSE (MFS-26245). Each program models slightly different manufacturing scenario. Written in Turbo C v2.0 for IBM PC-series and compatible computers running MS-DOS and successfully compiled using Turbo C++ v3.0.

Schroer, Bernard J.↗

NASA's Integrated Instrument Simulator Suite for Atmospheric Remote Sensing from Spaceborne Platforms (ISSARS) and Its Role for the ACE and GPM Missions

Forward simulation is an indispensable tool for evaluation of precipitation retrieval algorithms as well as for studying snow/ice microphysics and their radiative properties. The main challenge of the implementation arises due to the size of the problem domain. To overcome this hurdle, assumptions need to be made to simplify compiles cloud microphysics. It is important that these assumptions are applied consistently throughout the simulation process. ISSARS addresses this issue by providing a computationally efficient and modular framework that can integrate currently existing models and is also capable of expanding for future development. ISSARS is designed to accommodate the simulation needs of the Aerosol/Clouds/Ecosystems (ACE) mission and the Global Precipitation Measurement (GPM) mission: radars, microwave radiometers, and optical instruments such as lidars and polarimeter. ISSARS's computation is performed in three stages: input reconditioning (IRM), electromagnetic properties (scattering/emission/absorption) calculation (SEAM), and instrument simulation (ISM). The computation is implemented as a web service while its configuration can be accessed through a web-based interface.

real-aperture instruments↗

Onboard Radar Processing Development for Rapid Response Applications

We are developing onboard processor (OBP) technology to streamline data acquisition on-demand and explore the potential of the L-band SAR instrument onboard the proposed DESDynI mission and UAVSAR for rapid response applications. The technology would enable the observation and use of surface change data over rapidly evolving natural hazards, both as an aid to scientific understanding and to provide timely data to agencies responsible for the management and mitigation of natural disasters. We are adapting complex science algorithms for surface water extent to detect flooding, snow/water/ice classification to assist in transportation/ shipping forecasts, and repeat-pass change detection to detect disturbances. We are near completion of the development of a custom FPGA board to meet the specific memory and processing needs of L-band SAR processor algorithms and high speed interfaces to reformat and route raw radar data to/from the FPGA processor board. We have also developed a high fidelity Matlab model of the SAR processor that is modularized and parameterized for ease to prototype various SAR processor algorithms targeted for the FPGA. We will be testing the OBP and rapid response algorithms with UAVSAR data to determine the fidelity of the products.

dual polarized data↗

Hierarchical Control of Distributed Battery Energy Storage System in a DC Microgrid

This paper presents a novel hierarchical control approach of a DC microgrid (DCMG) which is supplied by a distributed battery energy storage system (BESS). With this approach, all battery units distributed in the BESS can be controlled to discharge with accurate current sharing and state-of-charge (SoC) balancing. Similar to other hierarchical control approaches used in DCMGs, this approach consists of three levels: (1) primary control, (2) secondary control and (3) tertiary control. This work includes defining a unit control error (UCE) at the secondary control level and evaluating current sharing weights at tertiary control level. A centralized controller at secondary control level is designed to detect the UCEs of each battery unit, and to restore the average voltage of a DCMG and control battery current sharing simultaneously. The distributed battery units share the load current in a DCMG based on weights. These weights are evaluated at the tertiary control level based on battery SoCs. The approach’s effectiveness was confirmed in digital simulation tests with the same simulation model as used in the NASA AMPS Modular Hardware Emulator.

Jing Zhang↗

A Tutorial on the Synthesis and Validation of a Closed-Loop Wind Farm Controller Using a Steady-State Surrogate Model

In wind farms, wake interaction leads to losses in power capture and accelerated structural degradation when compared to freestanding turbines. One method to reduce wake losses is by misaligning the rotor with the incoming flow using its yaw actuator, thereby laterally deflecting the wake away from downstream turbines. However, this demands an accurate and computationally tractable model of the wind farm dynamics. This problem calls for a closed-loop solution. This tutorial paper fills the scientific gap by demonstrating the full closed-loop controller synthesis cycle using a steady-state surrogate model. Furthermore, a novel, computationally efficient and modular communication interface is presented that enables researchers to straight-forwardly test their control algorithms in large-eddy simulations. High-fidelity simulations of a 9-turbine farm show a power production increase of up to 11% using the proposed closed-loop controller compared to traditional, greedy wind farm operation.

17 WIND ENERGY↗

MeVPrtl: An Event Generator for Dark Sector Particles in the Short-Baseline Neutrino Program

MeVPrtl is a modular event generator of beyond the Standard Model (BSM) physics particles developed for use in the Short-Baseline Neutrino (SBN) Program. A large class of BSM physics models predict that new particles could be produced in the intense Booster Neutrino Beam (BNB) and Neutrinos at the Main Injector (NuMI) beams at Fermilab, travel to the SBN Program detectors, and decay into Standard Model (SM) particles. These new physics models are motivated by dark matter, the neutrino mass scale, and a solution to the strong CP problem. MeVPrtl provides an interface to implement the overlapping phenomenology of these models, and to connect them with meson flux inputs and object outputs used by the SBN Program's LArSoft-based detector simulation. Implementations for the Higgs portal, heavy neutral lepton, and heavy QCD axion models exist within MeVPrtl. In this paper these implementations and their validation, as well as details of the MeVPrtl interface, are specified.

Abratenko Ao, P.↗

Modeling and simulation of Ultrasonic Guided Waves propagation in the fluid-structure domain by a monolithic approach

The present study introduces the coupled multiphysics model as part of the structural health monitoring (SHM) system. In particular, the Ultrasonic Guided Waves (UGWs) propagation is tracked in order to identify the damage to the structure. For this purpose, a multiphysics mathematical model is proposed. The model constitutes a monolithically coupled system of acoustic and elastic wave equations (WpFSI problem) where the wave signal displacement measurements are analyzed as the UGWs propagates in the solid, fluid and their interface. The ultimate goal of this paper is to explore and develop the efficient numerical solution of the WpFSI problem using the finite element method. A detailed description of the modeling framework and conditions that facilitate the coupling is provided. To couple the displacement-based acoustic wave equations for the isothermal fluid with elastic wave equations for the Saint Venant-Kirchhoff material model, the present study uses a monolithic solution algorithm. In particular, at each time step, wave equations are transformed to a fixed reference configuration via the arbitrary Lagrangian-Eulerian (ALE) mapping and automatically adopt the boundary conditions from the previous time step. The implementation is accomplished via the finite element library deal.II (Goll et al., 2017) based software toolbox DOpElib (Bangerth et al., 2007) which provides modularized higher level algorithms. Beyond SHM systems, the model is relevant for problems from biomechanics and biomedicine, vibromechanics, poroelasticity as well as subsurface and porous media flow. Here, the model developed here serves as a first step towards the on-line SHM system modeling, where structural dynamics are accounted for.

42 ENGINEERING↗

A modular methodology for time-domain stochastic seismic wave propagation

Presented here is a modular methodology for time-domain stochastic seismic wave propagation analysis. Presented methodology is designed to analyse uncertain seismic motions as an input, propagating through uncertain material. Traditional approach for uncertain wave propagation relies on models that include deep bedrock, local soil site, and their random process and random field information. Such models can become quite large and computationally intractable. The modular approach proposed herein features two step approach that allows separate consideration of the deep bedrock and local site along with corresponding random field information. In this work, the first step considers an auxiliary stochastic motions problem in the bedrock. Stochastic local site response can then be simulated in a reduced domain within certain depth from the surface. Application of uncertain seismic motions at depth, for local uncertain site response is done using stochastic effective forces developed through the Domain Reduction Method. By using Hermite polynomial chaos expansion to represent the non-Gaussian random field of material parameters and non-stationary random process of seismic motion, the proposed modular methodology is formulated using intrusive stochastic Galerkin approach, as seen in the Stochastic Elastic–Plastic Finite Element Method (SEPFEM). Developed modular methodology is illustrated using a 1-D stochastic seismic wave propagation analysis with three cases, and simulation results are also verified with results from conventional approach.

58 GEOSCIENCES↗

Modular Adaptive Packing for Integrally Cooled Absorbers

Process intensification is one cornerstone in ION Clean Energy’s (ION) efforts to lowering CO2 capture cost. ION has modeled, designed, and fabricated an innovative gas-liquid contactor known as Modular Adaptive Packing (MAP). During two successful SBIR Phase I and II projects entitled: “Rapid Design and Testing of Novel Gas-Liquid Contacting Devices for Post-Combustion CO2 Capture via 3D-printing”, ION developed and proved this new technology at bench scale. MAP, a 3D-printed lattice-structured packing, combines the absorber gas/liquid contactor with an innovative in-situ heat-exchanger. Thanks to the capabilities of 3D-printing, the lattice structure of MAP contains hollow channels through which coolant water can be pumped to remove the heat of reaction from CO2 absorption. ION refers to this novel method of heat exchange as intracooling. After 25.4 cm (10 in) diameter MAP modules were fabricated, ION built and tested a packing characterization rig at its pilot facility in Boulder, Colorado, U.S.A. To provide baseline results for the characterization rig, ION tested Sulzer’s Mellapak™ 250Y (MP250Y) as a standard structured packing. ION’s MAP was then compared directly to the baseline MP250Y packing to evaluate key indicators including pressure drop, liquid hold-up, and effective area. MAP has a higher pressure drop than MP250Y at the same gas velocities in addition to greater liquid holdup. However, ION found that MAP displays a higher wetting coverage of 93% compared to 65% for MP250Y and reduces shearing forces that result in undesirable droplet formation. Using Optimized Gas Treating’s (OGT) rate-based simulation software ProTreat®, a conceptual evaluation of MAP was modeled for a CO2 absorber using 30 wt% MEA solvent over a range of lean loadings at 90% CO2 capture from a coal-fired power plant. ION modeled a 25-meter column absorber for both the standard MP250Y packing and a hybrid column. The hybrid absorber contained 10 m of MP250Y packing at the top and bottom with the middle 5 meters comprised of MAP. Compared to a traditional intercooled absorber, MAP can remove 22% more heat and increase overall MEA carrying capacity by 4% without increasing overall pressure drop.

20 FOSSIL-FUELED POWER PLANTS↗

Large-scale Multiphysics Simulations of Small Modular Reactors Operating in Natural Circulation

Thanks to the advancements in high-performance computing, advanced modeling and simulation have become crucial in driving the development and deployment of next-generation nuclear reactors, such as small modular reactors (SMRs). SMRs offer the promise of cost-effective baseload electricity production and improved safety, while addressing some of the challenges associated with large reactor designs, such as high capital costs and extended construction timelines. As part of the Exascale Computing Project, the large-scale multiphysics simulation of an entire SMR primary system has been achieved by combining computational fluid dynamics and neutronics. In addition to the successful demonstration of full-core SMR simulations, the current study integrated the impact of natural circulation into the system. Natural circulation is the primary mechanism driving coolant circulation in SMRs. The mass flow rate in the core depends on the core power, and a numerical model has been developed to predict it. The pressure drop caused by the helical coil steam generator was also accounted for by developing a pressure drop correlation based on high-fidelity large eddy simulation results, further improving prediction accuracy. In conclusion, the results of the study demonstrate that the implemented natural circulation model is effective in predicting the responses of SMR full-core multiphysics simulations.

ECP↗

In vitro prototyping of limonene biosynthesis using cell-free protein synthesis

Metabolic engineering of microorganisms to produce sustainable chemicals has emerged as an important part of the global bioeconomy. Unfortunately, efforts to design and engineer microbial cell factories are challenging because design-build-test cycles, iterations of re-engineering organisms to test and optimize new sets of enzymes, are slow. To alleviate this challenge, we demonstrate a cell-free approach termed in vitro Prototyping and Rapid Optimization of Biosynthetic Enzymes (or iPROBE). In iPROBE, a large number of pathway combinations can be rapidly built and optimized. The key idea is to use cell-free protein synthesis (CFPS) to manufacture pathway enzymes in separate reactions that are then mixed to modularly assemble multiple, distinct biosynthetic pathways. As a model, we apply our approach to the 9-step heterologous enzyme pathway to limonene in extracts from Escherichia coli. In iterative cycles of design, we studied the impact of 54 enzyme homologs, multiple enzyme levels, and cofactor concentrations on pathway performance. In total, we screened over 150 unique sets of enzymes in 580 unique pathway conditions to increase limonene production in 24 h from 0.2 to 4.5 mM (23–610 mg/L). Finally, to demonstrate the modularity of this pathway, we also synthesized the biofuel precursors pinene and bisabolene. Finally, we anticipate that iPROBE will accelerate design-build-test cycles for metabolic engineering, enabling data-driven multiplexed cell-free methods for testing large combinations of biosynthetic enzymes to inform cellular design.

59 BASIC BIOLOGICAL SCIENCES↗

Rapid ISS Power Availability Simulator

The ISS (International Space Station) Power Resource Officers (PROs) needed a tool to automate the calculation of thousands of ISS power availability simulations used to generate power constraint matrices. Each matrix contains 864 cells, and each cell represents a single power simulation that must be run. The tools available to the flight controllers were very operator intensive and not conducive to rapidly running the thousands of simulations necessary to generate the power constraint data. SOLAR is a Java-based tool that leverages commercial-off-the-shelf software (Satellite Toolkit) and an existing in-house ISS EPS model (SPEED) to rapidly perform thousands of power availability simulations. SOLAR has a very modular architecture and consists of a series of plug-ins that are loosely coupled. The modular architecture of the software allows for the easy replacement of the ISS power system model simulator, re-use of the Satellite Toolkit integration code, and separation of the user interface from the core logic. Satellite Toolkit (STK) is used to generate ISS eclipse and insulation times, solar beta angle, position of the solar arrays over time, and the amount of shadowing on the solar arrays, which is then provided to SPEED to calculate power generation forecasts. The power planning turn-around time is reduced from three months to two weeks (83-percent decrease) using SOLAR, and the amount of PRO power planning support effort is reduced by an estimated 30 percent.

Downing, Nicholas↗

Modular supply chain optimization considering demand uncertainty to manage risk

Supply chain under demand uncertainty has been a challenging problem due to increased competition and market volatility in modern markets. Flexibility in planning decisions makes modular manufacturing a promising way to address this problem. We report the problem of multiperiod process and supply chain network design is considered under demand uncertainty. A mixed integer two-stage stochastic programming problem is formulated with integer variables indicating the process design and continuous variables to represent the material flow in the supply chain. The problem is solved using a rolling horizon approach. Benders decomposition is used to reduce the computational complexity of the optimization problem. To promote risk-averse decisions, a downside risk measure is incorporated in the model. The results demonstrate the several advantages of modular designs in meeting product demands. A pareto-optimal curve for minimizing the objectives of expected cost and downside risk is obtained.

42 ENGINEERING↗

elm-diagnostics

elm-diagnostics is a Python package for computing diagnostic analyses and visualizations for the E3SM Land Model (ELM) component and is meant to support new feature development in ELM. The tool reads model history files and performs quantitative analyses including budget-closure checking, variable transformations, temporal aggregations, and statistical summaries to support model evaluation, validation, and scientific interpretation. The framework is designed for extensibility, with modular architecture enabling straightforward addition of new diagnostic methods, derived variables, analysis types, visualization approaches, and model-specific adaptations

Hoffman, Matt [Los Alamos National Laboratory]↗

Design of Software for Design of Finite Element for Structural Analysis

The concepts of software engineering which allow a user of the finite element method to describe a model, to collect and to check the model data in a data base as well as to form the matrices required for a finite element calculation are examined. Next the components of the model description are conceived including the mesh tree, the topology, the configuration, the kinematic boundary conditions, the data for each element, and the loads. The possibilities for description and review of the data are considered. The concept of the segments for the modularization of the programs follows the components of the model description. The significance of the mesh tree as a globular guiding structure will be understood in view of the principle of the unity of the model, the mesh tree, and the data base. The user-friendly aspects of the software system will be summarized: the principle of language communication, the data generators, error processing, and data security.

Helfrich, Reinhard↗

Modeling and Harmonic Stability of MMC-HVDC With Passive Circulating Current Filters

A modular multilevel converter (MMC) is an emerging converter technology widely used in wind power applications using high-voltage direct current (HVDC) transmission, and it has been largely investigated in medium-voltage solar harvesting as well as electric motor drives. Different from studies dealing with active circulating current control loops, this paper focuses on impedance modeling and harmonic stability studies for MMCs with passive circulating current filters (PCCFs). A power stage circuit including a PCCF is transformed and remodeled to obtain small-signal formulations. This transformation leads to additional high-order matrix computing complexity due to the added impedance subnetwork matrix from the PCCF as well as relevant crossed-frequency impacts. To simplify the computational burden, the proposed model aims to solve one arm equation instead of all six MMC arm equations. To achieve this result, additional challenges occur when the MMC is connected to a renewable energy source instead of the grid voltage, where low-level zero-sequence components might exist in the neutral point of three phases, especially in the case of no integrated advanced modular voltage balancing control, which prevents computational simplification. To overcome this challenge, further impedance matrix adjustments are conducted in this paper to theoretically suppress the impact of zero-sequence harmonics when obtaining small-signal impedance, taking into account the frequency coupling effect. Finally, simulations are carried out to validate the developed impedance model under different operating scenarios. Harmonic stability case studies of MMCs with PCCFs connected to renewable energy current sources are also presented, where frequency-domain stability analyses based on Bode diagrams are compared to time-domain simulation waveforms and FFTs, which validate the effectiveness of the proposed impedance model.

24 POWER TRANSMISSION AND DISTRIBUTION↗