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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

HPC Network Simulation Tuning via Automatic Extraction of Hardware Parameters

Popular HPC network interconnection simulators such as SST/macro provide a variety of configurable parameters to explore the design space of hardware components such as network interface cards (NIC), switches, and links among them. While such knobs provide flexibility to explore design trade-offs for novel hardware, manually configuring simulations for matching configurations of the existing hardware to focus on topology exploration can be cumbersome and error-prone, leading to widely inaccurate simulations. This challenge is compounded when specifications of various (proprietary) technologies are not readily available or intentionally omitted. In this work, we propose a framework to autotune the multiple network models’ simulation configurations within SST/macro using Tree-structured Parzen Estimator-based Bayesian optimization to observe the effect on simulation accuracy across different message regimes. These regimes consist of small to large message sizes and latency to bandwidth-bound messages. We provide a detailed analysis of the simulation error for four representative HPC systems. Our Bayesian optimization based autotuning framework for network models achieves a maximum of 5x improvement in accuracy over best-effort manual configurations based on available hardware specifications.

Simulation, autotuning↗
NASA NTRS1986

Rapid torque-limited line-of-sight pointing of SCOLE (Spacecraft Control Laboratory Experiment) configuration

The design concept of a control for rapid torque-limited slewing of a rigid-mast version of the NASA SCOLE configuration is presented and demonstrated by means of numerical simulation. The time-optimal control problem for the system is decomposed into separate single-axis problems, expanding analytically the implicit nonlinear transcendental expression for the SCOLE line-of-sight error, and the final Euler attitude angles and slew angles are determined. The simulation results are presented in tables and graphs, and it is found that bang-bang or bang-pause-bang slew maneuvers with control moment applied to the Shuttle and control force applied to the reflector, and with a 5-deg/s slew-rate limit, produce the best pointing accuracy and the shortest slew times, although the specified line-of-sight error of 0.02 deg cannot be achieved using such open-loop single-axis maneuvers.

Lin, J. G.↗
NASA NTRS1991

Analytical modeling and sensor monitoring for optimal processing of polymeric composite material systems

Process simulation models and cure monitoring sensors are discussed for use in optimal processing of fiber-reinforced composites. Analytical models relate the specified temperature and pressure cure cycle to the thermal, chemical, and physical processes occurring in the composite during consolidation and cure. Frequency-dependent electromagnetic sensing (FDEMS) is described as an in situ sensor for monitoring the composite curing process and for verification of process simulation models. A model for resin transfer molding of textile composites is used to illustrate the predictive capabilities of a process simulation model. The model is used to calculate the resin infiltration time, fiber volume fraction, resin viscosity, and resin degree of cure. Results of the model are compared with in situ FDEMS measurements.

Loos, Alfred C.↗
DOE OSTI2025

Lie-algebraic classical simulations for quantum computing

The classical simulation of quantum dynamics plays an important role in our understanding of quantum complexity and in the development of quantum technologies. Efficient techniques such as those based on the Gottesman-Knill theorem for Clifford circuits, tensor networks for low entanglement-generating circuits, or Wick's theorem for fermionic Gaussian states have become central tools in quantum computing. In this work, we contribute to this body of knowledge by presenting a framework for classical simulations, dubbed “𝔤-sim”, which is based on the underlying Lie algebraic structure of the dynamical process. When the dimension of the algebra grows at most polynomially in the system size, there exist observables for which the simulation is efficient. Indeed, we show that 𝔤-sim enables new regimes for classical simulations, is able to deal with certain forms of noise in the evolution, as well as can be used to tackle several paradigmatic variational and nonvariational quantum computing tasks. For the former, we perform Lie-algebraic simulations to train and optimize parametrized quantum circuits (thus effectively showing that some variational models can be dequantized), design enhanced parameter initialization strategies, solve tasks of quantum circuit synthesis, and train a quantum-phase classifier. For the latter, we report large-scale noiseless and noisy simulations on benchmark problems. By comparing the limitations of 𝔤-sim and certain Wick's theorem-based simulations, we find that the two methods become inefficient for different types of states or observables, hinting at the existence of distinct, nonequivalent resources for classical simulation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Numerical derivative techniques for trajectory optimization

The adoption of robust numerical optimization techniques in trajectory simulation programs has resulted in powerful design and analysis tools. These trajectory simulation/optimization programs are widely used, and a representative list includes the GTS system, the POST program, and newer collocation methods such as OTIS and FONPAC. All of these programs rely on optimization algorithms which require objective function and constraint gradient data during the iteration process. However, most trajectory optimization problems lack simple analytical expressions for these derivatives. In the general case a function evaluation involves integrating aerodynamic, propulsive, and gravity forces over multiple trajectory phases with complex control models. With the newer collocation methods, the integration is replaced by defect constraints and cubic approximations for the state. While analytic gradient expressions can sometimes be derived for trajectory optimization problems, the derivation is cumbersome, time consuming, and prone to mistakes. Fortunately, an alternate method exists for the gradient evaluation, namely finite difference approximations. In this paper some finite difference gradient techniques developed for use with the GTS system are presented. These techniques include methods for computing first and second partial derivatives of single and multiple sets of functions. A key feature of these methods is an error control mechanism which automatically adjusts the perturbation size to obtain accurate derivative values.

Hallman, Wayne P.↗
NASA NTRS2001

Multidisciplinary Design Optimization of a Full Vehicle with High Performance Computing

Multidisciplinary design optimization (MDO) of a full vehicle under the constraints of crashworthiness, NVH (Noise, Vibration and Harshness), durability, and other performance attributes is one of the imperative goals for automotive industry. However, it is often infeasible due to the lack of computational resources, robust simulation capabilities, and efficient optimization methodologies. This paper intends to move closer towards that goal by using parallel computers for the intensive computation and combining different approximations for dissimilar analyses in the MDO process. The MDO process presented in this paper is an extension of the previous work reported by Sobieski et al. In addition to the roof crush, two full vehicle crash modes are added: full frontal impact and 50% frontal offset crash. Instead of using an adaptive polynomial response surface method, this paper employs a DOE/RSM method for exploring the design space and constructing highly nonlinear crash functions. Two NMO strategies are used and results are compared. This paper demonstrates that with high performance computing, a conventionally intractable real world full vehicle multidisciplinary optimization problem considering all performance attributes with large number of design variables become feasible.

Yang, R. J.↗
DOE OSTI2026

Joint Optimization of Multimodal Transit Frequency and Shared Autonomous Vehicle Fleet Size with Hybrid Metaheuristic and Nonlinear Programming

Shared autonomous vehicles (SAVs) bring competition to traditional transit services but redesigning multimodal transit network can utilize SAVs as feeders to enhance service efficiency and coverage. This paper presents an optimization framework for the joint multimodal transit frequency and SAV fleet size problem, a variant of the transit network frequency setting problem. The objective is to maximize total transit ridership (including SAV-fed trips and subtracting boarding rejections) across multiple time periods under budget constraints, considering endogenous mode choice (transit, point-to-point SAVs, driving) and route selection, while allowing for strategic route removal by setting frequencies to zero. Due to the problem’s non-linear, non-convex nature and the computational challenges of large-scale networks, we develop a hybrid solution approach that combines a metaheuristic approach (particle swarm optimization) with nonlinear programming for local solution refinement. To ensure computational tractability, the framework integrates analytical approximation models for SAV waiting times based on fleet utilization, multimodal network assignment for route choice, and multinomial logit mode choice behavior, bypassing the need for computationally intensive simulations within the main optimization loop. Applied to the Chicago metropolitan area’s multimodal network, our method illustrates a 33.3% increase in transit ridership through optimized transit route frequencies and SAV integration, particularly enhancing off-peak service accessibility and strategically reallocating resources.

Ng, Max↗
NASA NTRS2011

Constructive Engineering of Simulations

Joint experimentation that investigates sensor optimization, re-tasking and management has far reaching implications for Department of Defense, Interagency and multinational partners. An adaption of traditional human in the loop (HITL) Modeling and Simulation (M&S) was one approach used to generate the findings necessary to derive and support these implications. Here an entity-based simulation was re-engineered to run on USJFCOM's High Performance Computer (HPC). The HPC was used to support the vast number of constructive runs necessary to produce statistically significant data in a timely manner. Then from the resulting sensitivity analysis, event designers blended the necessary visualization and decision making components into a synthetic environment for the HITL simulations trials. These trials focused on areas where human decision making had the greatest impact on the sensor investigations. Thus, this paper discusses how re-engineering existing M&S for constructive applications can positively influence the design of an associated HITL experiment.

Snyder, Daniel R.↗
NASA NTRS2021

Modeling of Guided Waves for Aerospace Applications

Advancements in computer hardware has led to new possibilities for rapid modeling and simulation capabilities across many scientific fields. Nondestructive evaluation (NDE) can benefit from increased use of simulation tools to guide optimization of inspection and health monitoring methods, enhance understanding of data, aid in development of defect characterization methods, and generate data sets for use with machine learning and model-assisted probability of detection. Recent work at NASA has entailed development and benchmarking of both custom simulation codes and commercial simulation tools for ultrasonic wave propagation. This paper describes recent work at NASA in modeling of guided waves in composites and other aerospace materials. Results and computational speeds for a composite benchmark case are reported for a custom finite difference Rotated Staggered Grid code and for the commercial finite element software package, Pogo. Recent progress in linking NDE models to parametric analysis tools is also discussed.

Nondestructive evaluation↗
DOE OSTI2025

Development of a high fidelity CFD model for solvent evaporation and transport in porous structure during battery electrode drying

An efficient battery manufacturing process is the key to the mass production of Electric Vehicles (EV), in which drying is one of the most energy-intensive steps significantly influencing the battery cell performance. An accurate 3D CFD model for drying is essential for predicting the drying mechanism and optimizing its parameters. By optimizing the drying process, it is possible to reduce energy consumption and cost during battery manufacturing, minimize binder loading and maximize active material loading to achieve superior electrochemical performances and facilitate wider and faster public adoption of EV. This project aims to optimize the drying process during electrode manufacturing by leveraging high-fidelity, porous electrode simulations for solvent evaporation. By optimizing this process, we seek to reduce energy consumption during battery manufacturing, while minimizing binder loading and maximizing active material loading, with the overall goal of enhancing electrical vehicle performance.

Horner, Jeffrey Scott [Sandia National Laboratorie↗
NASA NTRS2005

Software for Engineering Simulations of a Spacecraft

Spacecraft Engineering Simulation II (SES II) is a C-language computer program for simulating diverse aspects of operation of a spacecraft characterized by either three or six degrees of freedom. A functional model in SES can include a trajectory flight plan; a submodel of a flight computer running navigational and flight-control software; and submodels of the environment, the dynamics of the spacecraft, and sensor inputs and outputs. SES II features a modular, object-oriented programming style. SES II supports event-based simulations, which, in turn, create an easily adaptable simulation environment in which many different types of trajectories can be simulated by use of the same software. The simulation output consists largely of flight data. SES II can be used to perform optimization and Monte Carlo dispersion simulations. It can also be used to perform simulations for multiple spacecraft. In addition to its generic simulation capabilities, SES offers special capabilities for space-shuttle simulations: for this purpose, it incorporates submodels of the space-shuttle dynamics and a C-language version of the guidance, navigation, and control components of the space-shuttle flight software.

Shireman, Kirk↗
NASA NTRS1988

Analysis procedures and subjective flight results of a simulator validation and cue fidelity experiment

A joint experiment to investigate simulator validation and cue fidelity was conducted by the Dryden Flight Research Facility of NASA Ames Research Center (Ames-Dryden) and NASA Langley Research Center. The primary objective was to validate the use of a closed-loop pilot-vehicle mathematical model as an analytical tool for optimizing the tradeoff between simulator fidelity requirements and simulator cost. The validation process includes comparing model predictions with simulation and flight test results to evaluate various hypotheses for differences in motion and visual cues and information transfer. A group of five pilots flew air-to-air tracking maneuvers in the Langley differential maneuvering simulator and visual motion simulator and in an F-14 aircraft at Ames-Dryden. The simulators used motion and visual cueing devices including a g-seat, a helmet loader, wide field-of-view horizon, and a motion base platform.

Carr, Peter C.↗
NASA NTRS2003

A Comparison of Techniques for Scheduling Fleets of Earth-Observing Satellites

Earth observing satellite (EOS) scheduling is a complex real-world domain representative of a broad class of over-subscription scheduling problems. Over-subscription problems are those where requests for a facility exceed its capacity. These problems arise in a wide variety of NASA and terrestrial domains and are .XI important class of scheduling problems because such facilities often represent large capital investments. We have run experiments comparing multiple variants of the genetic algorithm, hill climbing, simulated annealing, squeaky wheel optimization and iterated sampling on two variants of a realistically-sized model of the EOS scheduling problem. These are implemented as permutation-based methods; methods that search in the space of priority orderings of observation requests and evaluate each permutation by using it to drive a greedy scheduler. Simulated annealing performs best and random mutation operators outperform our squeaky (more intelligent) operator. Furthermore, taking smaller steps towards the end of the search improves performance.

Globus, Al↗
NASA NTRS2009

NASA Tech Briefs, December 2009

Topics include: A Deep Space Network Portable Radio Science Receiver; Detecting Phase Boundaries in Hard-Sphere Suspensions; Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery; Very-Long-Distance Remote Hearing and Vibrometry; Using GPS to Detect Imminent Tsunamis; Stream Flow Prediction by Remote Sensing and Genetic Programming; Pilotless Frame Synchronization Using LDPC Code Constraints; Radiometer on a Chip; Measuring Luminescence Lifetime With Help of a DSP; Modulation Based on Probability Density Functions; Ku Telemetry Modulator for Suborbital Vehicles; Photonic Links for High-Performance Arraying of Antennas; Reconfigurable, Bi-Directional Flexfet Level Shifter for Low-Power, Rad-Hard Integration; Hardware-Efficient Monitoring of I/O Signals; Video System for Viewing From a Remote or Windowless Cockpit; Spacesuit Data Display and Management System; IEEE 1394 Hub With Fault Containment; Compact, Miniature MMIC Receiver Modules for an MMIC Array Spectrograph; Waveguide Transition for Submillimeter-Wave MMICs; Magnetic-Field-Tunable Superconducting Rectifier; Bonded Invar Clip Removal Using Foil Heaters; Fabricating Radial Groove Gratings Using Projection Photolithography; Gratings Fabricated on Flat Surfaces and Reproduced on Non-Flat Substrates; Method for Measuring the Volume-Scattering Function of Water; Method of Heating a Foam-Based Catalyst Bed; Small Deflection Energy Analyzer for Energy and Angular Distributions; Polymeric Bladder for Storing Liquid Oxygen; Pyrotechnic Simulator/Stray-Voltage Detector; Inventions Utilizing Microfluidics and Colloidal Particles; RuO2 Thermometer for Ultra-Low Temperatures; Ultra-Compact, High-Resolution LADAR System for 3D Imaging; Dual-Channel Multi-Purpose Telescope; Objective Lens Optimized for Wavefront Delivery, Pupil Imaging, and Pupil Ghosting; CMOS Camera Array With Onboard Memory; Quickly Approximating the Distance Between Two Objects; Processing Images of Craters for Spacecraft Navigation; Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System; Rover Slip Validation and Prediction Algorithm; Safety and Quality Training Simulator; Supply-Chain Optimization Template; Algorithm for Computing Particle/Surface Interactions; Cryogenic Pupil Alignment Test Architecture for Aberrated Pupil Images; and Thermal Transport Model for Heat Sink Design.

Source record↗
DOE OSTI2026

Arctic Deployment of a Fully Integrated Self-Powered Drifting Buoy Harvesting Wave Energy via a Triboelectric Nanogenerator

The Arctic Ocean remains one of the most poorly sampled regions on Earth, where improved in situ environmental monitoring is vital for advancing oceanographic and atmospheric studies. However, data collection efforts are constrained by the short operational lifespans and high costs of conventional systems. Drifting buoys powered by pendulum-driven wave energy harvesters offer a cost-effective alternative, yet earlier designs have neither been optimized for real-world wave conditions nor validated in the Arctic. In this study, we develop a self-powered drifting buoy that integrates a pendulum-driven triboelectric nanogenerator (TENG) system with a mechanical motion rectifier, a high-gear-ratio transmission, and power management circuits. Through coupled buoy–pendulum dynamic simulations and laboratory testing using a motion simulator, we identify an optimal pendulum mass of 1.6 kg (12.7% of total buoy weight) that maximizes energy output while maintaining buoy stability. Laboratory experiments achieved average power outputs of 12.7 mW under Arctic-like wave and temperature conditions. The system was successfully deployed in the Bering Sea, where it generated 11 J of energy in 3.1 m waves, marking the first Arctic deployment of a TENG-based drifting buoy for sea surface temperature monitoring. This work establishes a cost-effective framework for designing self-powered Arctic monitoring platforms and advances the feasibility of long-term environmental observations in real Arctic waters.

marine enerby↗
DOE OSTI2025

Selective capture and recovery of uranium oxide colloids from aqueous soil suspensions using high gradient magnetic filtration

High Gradient Magnetic Filtration (HGMF) is a promising method for the selective capture and recovery of uranium oxide from surface soils. To date, however, magnetic filtration of uranium oxide has only been demonstrated at a proof-of-principle scale using relatively small filters (<5 cm 3 ) at low flowrates (<60 mL/min). Here, to explore the efficacy of magnetic filtration of uranium oxide at a larger scale, a newly designed HGMF apparatus that is more than an order of magnitude larger than our earlier filters (106 cm 3 ) was designed, fabricated, and tested at relatively high flowrates. Filtration experiments were performed using aqueous uranium oxide particle suspensions with Arizona Road Dust (ARD) as a soil simulant. At a flowrate of 125 mL/min, the apparatus’ uranium capture rate was exceptionally high (96 %), but selectivity was poor due to the high rate of capture for diamagnetic soil constituents (e.g., 77 % for silicon). All particles were captured at a lower rate when the flowrate was increased to 250 mL/min, but uranium selectivity was significantly increased due to the more substantial reduction in diamagnetic particle capture (i.e., capture rate of 77 % and 15 % for uranium and silicon, respectively). When backwashing the apparatus at the same flowrates used during filtration experiments, the rate of uranium recovery tended to be fairly low. Nevertheless, higher flowrates (1 L/min) and sonication were both shown to be highly effective methods of increasing uranium recovery. Magnetic field simulations were also performed to investigate potential optimizations to the design of the apparatus. These simulations showed that the intensity of the applied magnetic field could be increased by increasing the thickness of the steel magnetic housing. Additionally, stochastic trajectory simulations were performed to investigate the potential mechanisms of particle capture.

HGMF↗
DOE OSTI2025

AutoFocus: AI/ML-driven real-time wavefront diagnostics to autonomously align and optimize X-ray optics

We present an integrated system that combines advanced wavefront diagnostics with artificial intelligence (AI) to automate and optimize X-ray optics at synchrotron beamlines. This system couples real-time wavefront sensing with AI-driven control algorithms to achieve precise beam alignment, stabilization, and performance optimization. A key feature is the use of multi-fidelity transfer learning, which enables knowledge gained from both real-world beamline optimizations and ultra-realistic digital twin simulations to be effectively applied to in situ optimization. By leveraging multi-objective bayesian optimization, the system continuously refines its performance, reducing optimization time and minimizing the need for manual adjustments. Designed for seamless deployment, it operates with existing beamline hardware and provides an intuitive graphical interface. Initial deployments at the advanced photon source beamlines have demonstrated its ability to enhance beam stability, improve reproducibility, and significantly streamline alignment procedures. This AI-enhanced control framework represents a significant step toward fully autonomous beamline operation in next-generation synchrotron facilities.

Rebuffi, Luca [Argonne National Laboratory (ANL), ↗
NASA NTRS1977

Modeling and Analysis of Power Processing Systems (MAPPS), initial phase 2

The overall objective of the program is to provide the engineering tools to reduce the analysis, design, and development effort, and thus the cost, in achieving the required performances for switching regulators and dc-dc converter systems. The program was both tutorial and application oriented. Various analytical methods were described in detail and supplemented with examples, and those with standardization appeals were reduced into computer-based subprograms. Major program efforts included those concerning small and large signal control-dependent performance analysis and simulation, control circuit design, power circuit design and optimization, system configuration study, and system performance simulation. Techniques including discrete time domain, conventional frequency domain, Lagrange multiplier, nonlinear programming, and control design synthesis were employed in these efforts. To enhance interactive conversation between the modeling and analysis subprograms and the user, a working prototype of the Data Management Program was also developed to facilitate expansion as future subprogram capabilities increase.

Yu, Y.↗