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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 163 records · Page 9

A Coupled Theoretical and Experimental Approach to Elucidating the Mechanisms of Methyl Esters

The goal of this project was to probe fundamental kinetics questions regarding the gas phase reactive behavior of oxygenates. In order to succeed, our program necessitated both the development of new experimental tools and the development of theory based kinetic models to explain the chemistry of oxygenate fuels. By using advanced hybrid additive manufacturing/ traditional manufacturing techniques to create specialized ceramic micro-reactors, the team was able to simulate extreme high-temperature environments with much greater precision and durability than was previously possible. These tiny, high-tech tubes allow researchers to capture and identify "fleeting" chemical species—molecules that exist for only a fraction of a millisecond—using sophisticated light sources and mass spectrometry. Additionally, the team supported the development of a tabletop VUV laser system for isomer detection without a synchrotron. Through this work, we have successfully mapped out the specific chemical pathways of various oxygen-rich fuels, solving long-standing mysteries about how these substances break down kinetically. Ultimately, this research provides the fundamental knowledge needed to design next-generation engines and fuels that are better for the environment.

09 BIOMASS FUELS↗

Application of a two-point exponential approximation method in optimizing rotorcraft airframe structures

The Fadel (1990) two-point exponential approximation technique for rotorcraft airframe structural optimization is presently examined by comparing its results with the well established linear and hybrid first-order methods. Attention is given to both the elastic-line and FEM models of an AH-1G airframe. The Direct Matrix Abstraction Programming Language is used to compute sensitivity derivatives and motivate the CONMIN optimizer to produce the design change.

Sareen, Ashish K.↗

Net-baryon diffusion in fluid-dynamic simulations of relativistic heavy-ion collisions

A hybrid (hydrodynamics + hadronic transport) theoretical framework is assembled to model the bulk dynamics of relativistic heavy-ion collisions at energies accessible in the Beam Energy Scan (BES) program at the Relativistic Heavy-Ion Collider (RHIC) and the NA61/SHINE experiment at CERN. The system's energy-momentum tensor and net baryon current are evolved according to relativistic hydrodynamics with finite shear viscosity and non-zero net baryon diffusion. Our hydrodynamic description is matched to a hadronic transport model in the dilute region. With this fully integrated theoretical framework, we present a pilot study of the hadronic chemistry, particle spectra, and anisotropic flow. Phenomenological effects of a non-zero net-baryon current and its diffusion on hadronic observables are presented for the first time. Furthermore, the importance of the hadronic transport phase is also investigated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

STEPS: A Portable Numerical Simulation Toolkit for Electrical Power System Dynamic Studies

Numerical simulation is the key technique for large scale power system analysis. Redistribution of global renewable power via international interconnections requires new simulation tools to study the interconnected systems with different nominal frequencies as a whole. In this paper we introduce an open source simulation toolkit for electrical power systems (STEPS) which is hosted at Github. Its kernel is coded in C++ with major functions of power flow and electro-mechanical dynamic simulation. Flexible options are provided and configurable to improve power flow solution and dynamic simulation. Common devices and models are supported in STEPS for AC/DC hybrid system studies. Studies of interconnected systems with different nominal frequencies is supported in STEPS for research of international interconnection. Application program interfaces are provided and wrapped with Python to enable high-level interfaces for general applications. STEPS is thread safe and parallel computation is supported in both kernel and script levels to accelerate simulation. It is portable and works on Windows and GNU/Linux platforms. Cases from small to large scale systems are thoroughly tested to validate the toolkit with commercial packages as benchmarks.

42 ENGINEERING↗

Could a bioenergy program stimulate electric vehicle market penetration? Potential impacts of biogas to electricity annual rebate program

Abstract The biogas‐to‐electricity pathway under the Renewable Fuel Standard (RFS) allows for Renewable Identification Number (RIN) credits to be generated when electricity produced from biogas is used in the transportation sector. Though approved as a general pathway, EPA has proposed multiple credit allocation methods to functionalize this pathway. This study describes and evaluates a potential credit allocation framework where vehicle manufacturers generate electricity RIN (E‐RIN) credits and use these credits to increase the sales of plug‐in electric vehicles (PEVs). Under this framework, manufacturers use part of the credit value to reimburse electricity generators, offsetting potential higher biogas electricity generation cost. The remaining credit value is passed on to consumers as an annual PEV rebate to stimulate PEV sales. An iterative simulation framework is developed to fulfill two tasks: (a) to estimate the annual rebate amounts and their upfront value to consumers based on various factors, such as vehicle mileage, E‐RIN equivalence value, and biogas capacity, and (b) to evaluate potential impacts of the E‐RIN program on electrification of the future light‐duty vehicles (LDVs) and energy use. The annual rebate amount varies by vehicle technology and could be up to $870/year for battery electric vehicles (BEVs) and range between $230 and 825/year for plug‐in hybrid electric vehicles (PHEVs) depending on the electric range. These per vehicle rebates decrease when demand for electricity exceeds biogas electricity availability. The effectiveness of the program as modeled here is subject to different factors, such as the E‐RIN equivalence value, biogas electricity generation cost, biogas electricity generation capacity, and consumers’ valuation of the E‐RIN rebate. Our modeling results indicate that an E‐RIN program has the potential to produce nearly $12 billion in E‐RIN credits annually and to significantly increase PEV annual sales by up to 2.3 million and the PEV population by about 19.7 million in 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

LCA-PyTorch

LCA-PyTorch is a code repository which contains PyTorch implementations of the Locally Competitive Algorithm (LCA), which is a biologically-plausible sparse coding model. LCA-PyTorch allows for the training, testing, and analysis of single layer LCA networks, multi-layer LCA networks, and hybrid LCA-based deep neural network models on a wide variety of applications and data types. LCA-PyTorch was developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning. LCA-PyTorch interfaces heavily with the open-source PyTorch Python package.

Teti, Michael↗

HiRel: Hybrid Automated Reliability Predictor (HARP) integrated reliability tool system, (version 7.0). Volume 2: HARP tutorial

The Hybrid Automated Reliability Predictor (HARP) integrated Reliability (HiRel) tool system for reliability/availability prediction offers a toolbox of integrated reliability/availability programs that can be used to customize the user's application in a workstation or nonworkstation environment. The Hybrid Automated Reliability Predictor (HARP) tutorial provides insight into HARP modeling techniques and the interactive textual prompting input language via a step-by-step explanation and demonstration of HARP's fault occurrence/repair model and the fault/error handling models. Example applications are worked in their entirety and the HARP tabular output data are presented for each. Simple models are presented at first with each succeeding example demonstrating greater modeling power and complexity. This document is not intended to present the theoretical and mathematical basis for HARP.

Rothmann, Elizabeth↗

Application of high-performance computing to numerical simulation of human movement

We have examined the feasibility of using massively-parallel and vector-processing supercomputers to solve large-scale optimization problems for human movement. Specifically, we compared the computational expense of determining the optimal controls for the single support phase of gait using a conventional serial machine (SGI Iris 4D25), a MIMD parallel machine (Intel iPSC/860), and a parallel-vector-processing machine (Cray Y-MP 8/864). With the human body modeled as a 14 degree-of-freedom linkage actuated by 46 musculotendinous units, computation of the optimal controls for gait could take up to 3 months of CPU time on the Iris. Both the Cray and the Intel are able to reduce this time to practical levels. The optimal solution for gait can be found with about 77 hours of CPU on the Cray and with about 88 hours of CPU on the Intel. Although the overall speeds of the Cray and the Intel were found to be similar, the unique capabilities of each machine are better suited to different portions of the computational algorithm used. The Intel was best suited to computing the derivatives of the performance criterion and the constraints whereas the Cray was best suited to parameter optimization of the controls. These results suggest that the ideal computer architecture for solving very large-scale optimal control problems is a hybrid system in which a vector-processing machine is integrated into the communication network of a MIMD parallel machine.

NASA Discipline Musculoskeletal↗

Yearly report for the period Jan. 2018 – Feb. 2019 IC Project: w17_faultprediction “Critical Stress in Earth”

The consequence of earthquake is usually catastrophic. Currently, we cannot determine when a fault is approaching failure due to either anthropogenic activities or tectonic movement. In an anthropogenically perturbed setting, the rate of physical changes on faults far exceeds most natural processes with currently unpredictable and unmeasurable results. In a tectonic setting we generally do not know where a fault is in the earthquake cycle beyond noting how long has passed since the last rupture, which is itself sometimes unknown. The Laboratory has therefore funded a multi million multi-year LDRD-DR program that comprises experiments, numerical modeling, and machine learning in order to develop and test a highly novel approach to probe the earthquake cycle and in particular, to detect and locate stressed faults that are approaching failure. For this program, modeling of a series of sheared granular layers undergoing stick-slip behavior using the EES-17’s Combined Finite-Discrete Element Method (FDEM) based code HOSS (Hybrid Optimization Software Suite) plays a pivotal role since numerical simulations of granular fault gouge allow for analysis of the mechanical behavior of the system at a level of spatial and temporal resolution not accessible experimentally, and also offer the possibility of identifying the most important parameters governing earthquake dynamics. The simulated data also provide very detailed stress, strain and motion information for machine learning purpose to predict earthquake. The code – HOSS – has been developed in Geophysics Group in LANL during the past ten years and is used to simulate the stick-slip behavior of granular fault gouge. One of the key feature of HOSS is that it is superior to pure finite element method and discrete element method and can provide very detailed evolvement information of granular fault gouge. Additionally, its parallel computing capability makes large scale earthquake gouge simulation possible. Taking these facts into account, and also because few other fully parallel FDEM code exists, this IC project allows LANL to stay at the forefront of earthquake gouge and granular material simulation in the world.

42 ENGINEERING↗

Operations research investigations of satellite power stations

A systems model reflecting the design concepts of Satellite Power Stations (SPS) was developed. The model is of sufficient scope to include the interrelationships of the following major design parameters: the transportation to and between orbits; assembly of the SPS; and maintenance of the SPS. The systems model is composed of a set of equations that are nonlinear with respect to the system parameters and decision variables. The model determines a figure of merit from which alternative concepts concerning transportation, assembly, and maintenance of satellite power stations are studied. A hybrid optimization model was developed to optimize the system's decision variables. The optimization model consists of a random search procedure and the optimal-steepest descent method. A FORTRAN computer program was developed to enable the user to optimize nonlinear functions using the model. Specifically, the computer program was used to optimize Satellite Power Station system components.

Cole, J. W.↗

Strengthening the SDP Relaxation of AC Power Flows with Convex Envelopes, Bound Tightening, and Valid Inequalities

Here this work revisits the Semidefine Programming (SDP) relaxation of the AC power flow equations in light of recent results illustrating the benefits of bounds propagation, valid inequalities, and the Convex Quadratic (QC) relaxation. By integrating all of these results into the SDP model a new hybrid relaxation is proposed, which combines the benefits from all of these recent works. This strengthened SDP formulation is evaluated on 71 AC Optimal Power Flow test cases from the NESTA archive and is shown to have an optimality gap of less than 1% on 63 cases. This new hybrid relaxation closes 50% of the open cases considered, leaving only 8 for future investigation.

42 ENGINEERING↗

Methodology for the Simulation of Molecular Motors at Different Scales

Millisecond-scale conformational transitions represent a seminal challenge for traditional molecular dynamics simulations, even with the help of high-end supercomputer architectures. Such events are particularly relevant to the study of molecular motors—proteins or abiological constructs that convert chemical energy into mechanical work. Here, we present a hybrid-simulation scheme combining an array of methods including elastic network models, transition path sampling, and advanced free-energy methods, possibly in conjunction with generalized-ensemble schemes to deliver a viable option for capturing the millisecond-scale motor steps of biological motors. The methodology is already implemented in large measure in popular molecular dynamics programs, and it can leverage the massively parallel capabilities of petascale computers. The applicability of the hybrid method is demonstrated with two examples, namely cyclodextrin-based motors and V-type ATPases.

Chemistry↗

Ultracompact hybrid stars consistent with multimessenger astrophysics

In this work, we consider the consequences of phase transition in dense QCD on the properties of compact stars and implications for the observational program in gravitational wave and x-ray astrophysics. The key underlying assumption of our modeling is a strong first-order phase transition past the point where the hadronic branch of compact stars reaches the two-solar mass limit. Furthermore, our analysis predicts ultracompact stars with very small radii—in the range of 6–9 km—living on compact star sequences that are entirely consistent with the current multimessenger data. We show that sequences featuring two-solar mass hadronic stars consistent with radio-pulsar observations are also consistent with the inferences of large radii for massive neutron stars by NICER x-ray observations of neutron stars and the small radii predicted by gravitational waves analysis of the binary neutron star inspiral event GW170817 for our models that feature a strong first-order QCD phase transition.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Multi-Scale Inference, Estimation, and Prediction Engine for Earth System Modeling

We posit that AI methods can be leveraged to significantly enhance the predictive skill of forward Earth system modeling (ESM) activities. A hybrid framework incorporating traditional ESM modeling, inference methods, and AI techniques could make better use of both measured and computed information as well as computational resources by targeting inference tasks at program priorities, such as the predictability of precipitation extremes. This runtime pathway to closing the simulation/analysis-data/model improvement loop will streamline the traditional offline pathway to model improvement, which is based on domain science expertise, while suggesting guidance for further observations and measurements.

58 GEOSCIENCES↗

Nonelastic nuclear reactions and accompanying gamma radiation

Several aspects of nonelastic nuclear reactions which proceed through the formation of a compound nucleus are dealt with. The full statistical model and the partial statistical model are described and computer programs based on these models are presented along with operating instructions and input and output for sample problems. A theoretical development of the expression for the reaction cross section for the hybrid case which involves a combination of the continuum aspects of the full statistical model with the discrete level aspects of the partial statistical model is presented. Cross sections for level excitation and gamma production by neutron inelastic scattering from the nuclei Al-27, Fe-56, Si-28, and Pb-208 are calculated and compared with avaliable experimental data.

Snow, R.↗

Predictive Battery Management System for Commercial Hybrid Vehicles: Cooperative Research and Development Final Report, CRADA Number CRD-13-520

NREL and Eaton Corporation will perform work together on DOE Advanced Research Projects Agency-Energy (ARPA-E) 'Advanced Management and Protection of Energy Storage Devices' program (DE-FOA0000675). NREL will experimentally characterize aging behavior of Eaton cells and packs. Eaton and NREL will implement NREL's prognostic life model in Eaton HEV supervisory controllers and demonstrate the algorithms in accelerated life hardware-in-the loop testing conducted at NREL.

25 ENERGY STORAGE↗

What Multilevel Parallel Programs do when you are not Watching: A Performance Analysis Case Study Comparing MPI/OpenMP, MLP, and Nested OpenMP

With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors, parallel programming techniques have evolved that support parallelism beyond a single level. When comparing the performance of applications based on different programming paradigms, it is important to differentiate between the influence of the programming model itself and other factors, such as implementation specific behavior of the operating system (OS) or architectural issues. Rewriting-a large scientific application in order to employ a new programming paradigms is usually a time consuming and error prone task. Before embarking on such an endeavor it is important to determine that there is really a gain that would not be possible with the current implementation. A detailed performance analysis is crucial to clarify these issues. The multilevel programming paradigms considered in this study are hybrid MPI/OpenMP, MLP, and nested OpenMP. The hybrid MPI/OpenMP approach is based on using MPI [7] for the coarse grained parallelization and OpenMP [9] for fine grained loop level parallelism. The MPI programming paradigm assumes a private address space for each process. Data is transferred by explicitly exchanging messages via calls to the MPI library. This model was originally designed for distributed memory architectures but is also suitable for shared memory systems. The second paradigm under consideration is MLP which was developed by Taft. The approach is similar to MPi/OpenMP, using a mix of coarse grain process level parallelization and loop level OpenMP parallelization. As it is the case with MPI, a private address space is assumed for each process. The MLP approach was developed for ccNUMA architectures and explicitly takes advantage of the availability of shared memory. A shared memory arena which is accessible by all processes is required. Communication is done by reading from and writing to the shared memory.

Jost, Gabriele↗