Search NASA⌕ Search

SEARCH · Search NASA

Results for “Simulation System”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Optimal Sizing and Placement of Battery Energy Storage in Distribution System Based on Solar Size for Voltage Regulation

This paper proposes a new strategy to achieve voltage regulation in distributed power systems in the presence of solar energy sources and battery storage systems. The goal is to find the minimum size of battery storage and its corresponding location in the network based on the size and place of the integrated solar generation. The proposed method formulates the problem by employing the network impedance matrix to obtain an analytical solution instead of using a recursive algorithm such as power flow. The required modifications for modeling the slack and PV buses (generator buses) are utilized to increase the accuracy of the approach. The use of reactive power control to regulate the voltage regulation is not always an optimal solution as in distribution systems R/X is large. In this paper the minimum size and the best place of battery storage is achieved by optimizing the amount of both active and reactive power exchanged by battery storage and its gridtie inverter (GTI) based on the network topology and R/X ratios in the distribution system. Simulation results for the IEEE 14-bus system verify the effectiveness of the proposed approach.

14 SOLAR ENERGY↗
DOE OSTI2018

NanoStructured bulk thermoelectric generator for efficient power harvesting for self-powered sensor network

The goal of the Nuclear Energy Enabling Technology Research Project is to develop efficient and reliable thermoelectric (TE) generators for self-powered wireless sensor nodes (WSNs) for nuclear applications. The power harvesting technology has crosscutting significance to all United States Department of Energy Office of Nuclear Energy research and development programs, as it will enable self-powered WSNs in multiple nuclear reactor designs and spent fuel storage facilities using thermal energy available in a nuclear power plant or spent fuel storage facility. This project addresses an important technology gap that exists in truly realizing WSNs due to the need for cables to connect to external power supplies and develop TE power harvesting devices to deliver sufficient power to drive the WSNs. The outcomes of the project will lead to significant advancement in sensors and instrumentation technology, reducing cost, improving monitoring reliability, and therefore enhancing safety. The self-powered WSNs could support the long-term safe and economical operation of all reactor designs and fuel cycle concepts, as well as spent fuel storage and many other nuclear science and engineering applications. The research is based on recent breakthroughs in high-performance nanostructured bulk (nanobulk) half-Heusler and bismuth telluride thermoelectric materials that enable high-efficiency and high-power-density direct heat-to-electricity conversion over a wide temperature range. The nanobulk TE materials that the research team has already developed yield up to a 50% increase in the TE figure of merit, ZT, compared with state-of-the-art bulk counterparts. In addition to increased efficiency, the nanostructured materials are of potentially enhanced radiation tolerance due to the increased interface densities at the nanoscale grain boundaries that serves as efficient sinks to annihilate radiation-induced, freely-migrating structural defects. This report summarizes major technical results the team achieved in this three-year project, with a focus on the results obtained in the third year of the project. The report includes results on thermoelectric materials fabrication and optimization, irradiation effect on thermoelectric materials performance, thermoelectric device simulation, fabrication and testing, wireless sensor node system simulation, and the demonstration of a wireless sensor node powered by thermoelectric generators.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

A geometric initial guess for localized electronic orbitals in modular biological systems

Recent first-principles molecular dynamics algorithms using localized electronic orbitals have achieved O(N) complexity and controlled accuracy in simulating systems with finite band gaps. However, accurately deter- mining the centers of these localized orbitals during simulation setup may require O(N 3 ) operations, which is computationally infeasible for many biological systems. We present an O(N) approach for approximating orbital centers in proteins, DNA, and RNA which uses non-localized solutions for a set of fixed-size subproblems to create a set of geometric maps applicable to larger systems. This scalable approach, used as an initial guess in the O(N) first-principles molecular dynamics code MGmol, facilitates first-principles simulations in biological systems of sizes which were previously impossible.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

NANDFlashSim: High-Fidelity, Microarchitecture-Aware NAND Flash Memory Simulation [NANDFlashSim: Intrinsic Latency Variation Aware NAND Flash Memory System Modeling and Simulation at Microarchitecture Level]

As the popularity of NAND flash expands in arenas from embedded systems to high-performance computing, a high-fidelity understanding of its specific properties becomes increasingly important. Further, with the increasing trend toward multiple-die, multiple-plane architectures and high-speed interfaces, flash memory systems are expected to continue to scale and cheapen, resulting in their broader proliferation. However, when designing NAND-based devices, making decisions about the optimal system configuration is nontrivial, because flash is sensitive to a number of parameters and suffers from inherent latency variations, and no available tools suffice for studying these nuances. The parameters include the architectures, such as multidie and multiplane, diverse node technologies, bit densities, and cell reliabilities. Therefore, we introduce NANDFlashSim, a high-fidelity, latency-variation-aware, and highly configurable NAND-flash simulator, which implements a detailed timing model for 16 state-of-the-art NAND operations. Using NANDFlashSim, we notably discover the following. First, regardless of the operation, reads fail to leverage internal parallelism. Second, MLC provides lower I/O bus contention than SLC, but contention becomes a serious problem as the number of dies increases. Third, many-die architectures outperform many-plane architectures for disk-friendly workloads. Lastly, employing a high-performance I/O bus or an increased page size does not enhance energy savings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A massively parallel and scalable multi-CPU material point method

Harnessing the power of modern multi-GPU architectures, we present a massively parallel simulation system based on the Material Point Method (MPM) for simulating physical behaviors of materials undergoing complex topological changes, self-collision, and large deformations. Our system makes three critical contributions. First, we introduce a new particle data structure that promotes coalesced memory access patterns on the GPU and eliminates the need for complex atomic operations on the memory hierarchy when writing particle data to the grid. Second, we propose a kernel fusion approach using a new Grid-to-Particles-to-Grid (G2P2G) scheme, which efficiently reduces GPU kernel launches, improves latency, and significantly reduces the amount of global memory needed to store particle data. Finally, we introduce optimized algorithmic designs that allow for efficient sparse grids in a shared memory context, enabling us to best utilize modern multi-GPU computational platforms for hybrid Lagrangian-Eulerian computational patterns. We demonstrate the effectiveness of our method with extensive benchmarks, evaluations, and dynamic simulations with elastoplasticity, granular media, and fluid dynamics. In comparisons against an open-source and heavily optimized CPU-based MPM codebase [Fang et al. 2019] on an elastic sphere colliding scene with particle counts ranging from 5 to 40 million, our GPU MPM achieves over 100x per-time-step speedup on a workstation with an Intel 8086K CPU and a single Quadro P6000 GPU, exposing exciting possibilities for future MPM simulations in computer graphics and computational science. Moreover, compared to the state-of-the-art GPU MPM method [Hu et al. 2019a], we not only achieve 2x acceleration on a single GPU but our kernel fusion strategy and Array-of-Structs-of-Array (AoSoA) data structure design also generalizes to multi-GPU systems. Our multi-GPU MPM exhibits near-perfect weak and strong scaling with 4 GPUs, enabling performant and large-scale simulations on a 10243 grid with close to 100 million particles with less than 4 minutes per frame on a single 4-GPU workstation and 134 million particles with less than 1 minute per frame on an 8-GPU workstation.

Wang, Xinlei↗
DOE OSTI2016

Plant-wide simulation model for transient studies on the XE-100 - 18464

This paper gives an overview of the plant-wide simulation model that is used by X-energy LLC for developing their plant design and control philosophy, as well as assessing plant upset conditions. The simulation model was created in Flownex{sup R} thermal-fluid system simulation software, which solves mass, momentum and energy equations for compressible, incompressible and homogeneous two-phase flow. The plant model encompasses all major components, from reactor to condenser, including main control loop elements. The paper pays particular attention to the validation of the two-phase flow framework used for the secondary steam cycle. Two steady-state validation cases are done using operational data from the THTR. Validation of transient operation is done by simulating density wave oscillations, a type of system-level boiling phenomenon. This is regarded as a thorough test of transient capability because of the challenges this phenomenon poses to several aspects of the calculation and to the consistency of the code as a whole. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Practical Understanding of Cancer Model Identifiability in Clinical Applications

Mathematical models are a core component in the foundation of cancer theory and have been developed as clinical tools in precision medicine. Modeling studies for clinical applications often assume an individual’s characteristics can be represented as parameters in a model and are used to explain, predict, and optimize treatment outcomes. However, this approach relies on the identifiability of the underlying mathematical models. In this study, we build on the framework of an observing-system simulation experiment to study the identifiability of several models of cancer growth, focusing on the prognostic parameters of each model. Our results demonstrate that the frequency of data collection, the types of data, such as cancer proxy, and the accuracy of measurements all play crucial roles in determining the identifiability of the model. We also found that highly accurate data can allow for reasonably accurate estimates of some parameters, which may be the key to achieving model identifiability in practice. As more complex models required more data for identification, our results support the idea of using models with a clear mechanism that tracks disease progression in clinical settings. For such a model, the subset of model parameters associated with disease progression naturally minimizes the required data for model identifiability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

A Hybrid Multiscale Framework for Subsurface Flow and Transport Simulations

Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, or system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application-specific and sometimes ad-hoc approaches for model coupling. We are developing a generalized approach to hierarchical model coupling designed for high-performance computational systems, based on the Swift computing workflow framework. In this presentation we will describe the generalized approach and provide two use cases: 1) simulation of a mixing-controlled biogeochemical reaction coupling pore- and continuum-scale models, and 2) simulation of biogeochemical impacts of groundwater – river water interactions coupling fine- and coarse-grid model representations. This generalized framework can be customized for use with any pair of linked models (microscale and macroscale) with minimal intrusiveness to the at-scale simulators. It combines a set of python scripts with the Swift workflow environment to execute a complex multiscale simulation utilizing an approach similar to the well-known Heterogeneous Multiscale Method. User customization is facilitated through user-provided input and output file templates and processing function scripts, and execution within a high-performance computing environment is handled by Swift, such that minimal to no user modification of at-scale codes is required.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A brain-plausible neuromorphic on-the-fly learning system implemented with magnetic domain wall analog memristors

Neuromorphic computing is an approach to efficiently solve complicated learning and cognition problems like the human brain using electronics. To efficiently implement the functionality of biological neurons, nanodevices and their implementations in circuits are exploited. Here, we describe a general-purpose spiking neuromorphic system that can solve on-the-fly learning problems, based on magnetic domain wall analog memristors (MAMs) that exhibit many different states with persistence over the lifetime of the device. The research includes micromagnetic and SPICE modeling of the MAM, CMOS neuromorphic analog circuit design of synapses incorporating the MAM, and the design of hybrid CMOS/MAM spiking neuronal networks in which the MAM provides variable synapse strength with persistence. Using this neuronal neuromorphic system, simulations show that the MAM-boosted neuromorphic system can achieve persistence, can demonstrate deterministic fast on-the-fly learning with the potential for reduced circuitry complexity, and can provide increased capabilities over an all-CMOS implementation.

42 ENGINEERING↗
DOE OSTI2025

Comparative performance assessment of air-source and ground-source heat pumps using CO₂ and R-410A with water well integration: A simulation study

This study investigates the performance and feasibility of heat pump systems for residential space heating in cold climates, with a particular focus on ground source heat pumps (GSHPs) with water wells. Four configurations are modeled and compared, a CO 2 air-source heat pump (ASHP), an R-410A ASHP, a CO 2 GSHP with water well integration, and an R-410A ground-source heat pump with water well integration. System simulations are conducted at both equipment and whole-building levels, followed by a nationwide analysis across ten representative cities using EnergyPlus. Results show that water-well-coupled GSHPs maintain approximately 87 % of their efficiency and 85.5 % of heating capacity as ambient temperature drops from 47 °F/8.3 °C to −15 °F/-26.1 °C, whereas ASHPs retain only 55 % efficiency and 44.5 % capacity. R-410A systems achieve higher efficiency, while CO 2 systems provide significant environmental advantages, including reduced risks of groundwater contamination from refrigerant leakage. On average, the CO 2 GSHPs deliver 35–45 % heating energy savings relative to ASHPs and demonstrate strong potential as a replacement for gas furnaces in cold climates. This work represents a systematic comparative assessment of CO 2 and R-410A air-source and ground-source heat pumps with water well integration. In conclusion, the findings highlight the technical viability, environmental benefits and deployment potential of CO 2 GSHPs, offering a pathway toward efficient and sustainable residential heating solutions in diverse U.S. climates.

CO 2 GSHP↗
DOE OSTI2025

Simulated annealing of reduced magnetohydrodynamic systems

Theory of simulated annealing (SA), a method for equilibrium and stability analyses for Hamiltonian systems, is reviewed. The SA explained in this review is based on a double bracket formulation that derives from Hamiltonian structure. In addition to general theoretical aspects, the explicit formulation as well as numerical applications are presented. Both finite and infinite degree-of-freedom systems are treated, in particular, the heavy top, a toy model mimicking low-beta reduced magnetohydrodynamics (MHD) and low- and high-beta reduced MHD. Furthermore, the numerical results successfully demonstrate the usefulness of SA for equilibrium and stability analyses. At the same time, the results raise some future issues that are discussed in the paper.

Poisson Bracket↗
DOE OSTI2026

infrastore [SWR-26-077]

Infrastore is time-series storage for energy-systems simulations, backed by HDF5 + SQLite, with Rust, Python, Julia, gRPC, and CLI bindings. It is a Rust library for managing time-series data in power-systems and energy simulations. Numerical arrays are persisted in HDF5, and the metadata associating each array with its owning component lives in SQLite. Identical arrays are stored once and shared through content addressing. It ships native Rust, Python (PyO3), and Julia (C ABI) interfaces, the infrastore command-line tool, and a read-only gRPC server with a Rust client. Documentation: https://natlabrockies.github.io/infrastore/latest/ — start with the Quick Start or the Architecture.

Thom, Daniel [National Laboratory of the Rockies (↗
DOE OSTI2021

Quasi-Static Time Series Fatigue Simulation for PV Inverter Semiconductors with Long-Term Solar Profile

Power system simulations with long-term data tend to have large time steps varying from one second to a few minutes. However, for PV inverter semiconductors, the minimum thermal stresses cycle is with line frequency. This requires the time step of the fatigue simulation to be much smaller than the line period. This small time step results in poor simulation speed, especially for long-term simulations. This paper proposes a fast fatigue simulation for inverter semiconductors using the quasi-static time series (QSTS) simulation concept. The fatigue analysis typically focuses on the peak and valley values of a strain and neglect the transients from peaks to valleys. The proposed simulation utilizes this property of fatigue analysis and calculates the steady state of the semiconductor junction temperature only. The resulting time step of the fatigue simulation is 15 minutes, which is consistent with the solar dataset without losing accuracy.

fast simulation↗
DOE OSTI2018

Assessing the capability of different satellite observing configurations to resolve the distribution of methane emissions at kilometer scales

Anthropogenic methane emissions originate from a large number of fine-scale and often transient point sources. Satellite observations of atmospheric methane columns are an attractive approach for monitoring these emissions but have limitations from instrument precision, pixel resolution, and measurement frequency. Dense observations will soon be available in both low-Earth and geostationary orbits, but the extent to which they can provide fine-scale information on methane sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) to assess the capabilities of different satellite observing system configurations. We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 × 1.3 km 2 spatial resolution and hourly temporal resolution over a 290 × 235 km 2 domain in the Barnett Shale, a major oil and gas field in Texas with a large number of point sources. We sub-sample these footprints to match the observing characteristics of the recently launched TROPOMI instrument (7 × 7 km 2 pixels, 11 ppb precision, daily frequency), the planned GeoCARB instrument (2.7 × 3.0 km 2 pixels, 4 ppb precision, nominal twice-daily frequency), and other proposed observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its eigenvalues. We find that a week of TROPOMI observations should provide information on temporally invariant emissions at ~30 km spatial resolution. GeoCARB should provide information available on temporally invariant emissions ~2–7 km spatial resolution depending on sampling frequency (hourly to daily). Improvements to the instrument precision yield greater increases in information content than improved sampling frequency. A precision better than 6 ppb is critical for GeoCARB to achieve fine resolution of emissions. Transient emissions would be missed with either TROPOMI or GeoCARB. An aspirational high-resolution geostationary instrument with 1.3 × 1.3 km 2 pixel resolution, hourly return time, and 1 ppb precision would effectively constrain the temporally invariant emissions in the Barnett Shale at the kilometer scale and provide some information on hourly variability of sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Simulation of Magnetic Systems in the Domain with a Corner

Numerical simulation of magnetic systems having corner points is considered. The literature on this topic is reviewed. A method of encapsulating the function behavior near corner points in the difference scheme is proposed for numerical solution of the 2D magnetostatic problem in the iron domain. For the 3D magnetostatic problem in the iron/vacuum domain, the increase in the magnetic field near the corner point is estimated, and a method for construction of an adaptive mesh is proposed. A parallel algorithm is implemented on the graphics-processing unit (GPU) architecture for faster search for the numerical solution of the magnetostatic problem. Numerical simulation is performed for the magnetic system of the SPD detector to be used at the NICA complex (JINR, Dubna).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Theory of Trotter Error with Commutator Scaling

The Lie-Trotter formula, together with its higher-order generalizations, provides a simple approach to decomposing the exponential of a sum of operators. Despite significant effort, the error scaling of such product formulas remains poorly understood. We develop a theory of Trotter error that overcomes the limitations of truncating the Baker-Campbell-Hausdorff expansion. Our analysis directly exploits the commutativity of operator summands, producing tighter error bounds for both real- and imaginary-time evolutions. Whereas previous work achieves similar goals for systems with geometric locality or Lie-algebraic structure, our approach holds in general. We give a host of improved algorithms for digital quantum simulation and quantum Monte Carlo methods, nearly matching or even outperforming the best previous results. Our applications include: (i) a simulation of second-quantized plane-wave electronic structure, nearly matching the interaction-picture algorithm of Low and Wiebe; (ii) a simulation of $k$-local Hamiltonians almost with induced one-norm scaling, faster than the qubitization algorithm of Low and Chuang; (iii) a simulation of rapidly decaying power-law interactions, outperforming the Lieb-Robinson-based approach of Tran et al.; (iv) a hybrid simulation of clustered Hamiltonians, dramatically improving the result of Peng, Harrow, Ozols, and Wu; and (v) quantum Monte Carlo simulations of the transverse field Ising model and quantum ferromagnets, tightening previous analyses of Bravyi and Gosset. We obtain further speedups using the fact that product formulas can preserve the locality of the simulated system. Specifically, we show that local observables can be simulated with complexity independent of the system size for power-law interacting systems, which implies a Lieb-Robinson bound nearly matching a recent result of Tran et al. Our analysis reproduces known tight bounds for first- and second-order formulas. We further investigate the tightness of our bounds for higher-order formulas. For quantum simulation of a one-dimensional Heisenberg model with an even-odd ordering of terms, our result overestimates the complexity by only a factor of $5$. Our bound is also close to tight for power-law interactions and other orderings of terms. This suggests that our theory can accurately characterize Trotter error in terms of both the asymptotic scaling and the constant prefactor.

quantum computing, numerical analysis↗