Search NASA⌕ Search

SEARCH · Search NASA

Results for “programming model”

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 1,801 records · Page 100
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

An optimization framework for workplace charging strategies

The workplace charging (WPC) has been recently recognized as the most important secondary charging point next to residential charging for plug-in electric vehicles (PEVs). The current WPC practice is spontaneous and grants every PEV a designated charger, which may not be practical or economic when there are a large number of PEVs present at workplace. This study is the first research undertaken that develops an optimization framework for WPC strategies to satisfy all charging demand while explicitly addressing different eligible levels of charging technology and employees’ demographic distributions. The optimization model is to minimize the lifetime cost of equipment, installations, and operations, and is formulated as an integer program. We demonstrate the applicability of the model using numerical examples based on national average data. The results indicate that the proposed optimization model can reduce the total cost of running a WPC system by up to 70% compared to the current practice. The WPC strategies are sensitive to the time windows and installation costs, and dominated by the PEV population size. The WPC has also been identified as an alternative sustainable transportation program to the public transit subsidy programs for both economic and environmental advantages.

Optimization↗
DOE OSTI2025

Root genetics in the field to understand drought adaptation and carbon sequestration (Final Scientific/Technical Report)

For all crop plants, roots play a critical role in growth. Roots anchor the plants, and are the primary site of nutrient and water uptake. Roots are also the main source of C to soil in the form of root tissues and exudates, and thus greatly influence SOM stocks. To perform these functions, primary roots extend into soil, producing a network of branching roots of characteristic form, known as its root system architecture (RSA). RSA varies among species, and among varieties within a species that are adapted to different environments. Root traits are major targets for the second green revolution because of their potential to improve crop productivity, increase drought tolerance and nutrient acquisition, and increase C capture of soil. Improving the quality of roots in maize will be particularly valuable, since this crop is planted on over 92 million acres annually in the US. The future sustainability of agricultural systems relies on their ability to enhance soil organic matter (SOM) storage and reduce GHG emissions, while maintaining or enhancing productivity. This program had two components, Sensors and Models. For the first component, we designed and built a high-throughput phenotyping platform for root pulling of maize plants. This eliminated the physical labor of manually pulling up plants and reduced the number of personnel required down to one. The standardized pulling mechanism allowed recording force curves during the pulling process, providing additional information. We validated that the maximum force for pulling the root system was well-correlated with the root system mass and provided root crowns for further RSA analysis. These root crowns identified significant correlations with 2D root area and root depth, along with 3D root volume, total root length and number of root tips. We then used this system for field-based studies in maize on the genetics of root system architecture and its relation to nitrogen-use efficiency (NUE), including using lines relevant to the Corteva breeding program. Varieties were also evaluated at Corteva sites in the cornbelt and Danforth farm in Missouri, to establish responses across sites. From these studies we have identified genetic loci associated with root traits and created mutant lines for these loci and correlations of root traits with NUE. For the Models component, we worked to incorporate root and soil characteristics into the MEMS 2.0 soil and ecosystem biogeochemical model. Existing soil C models, such as Century, are unable to represent specific root trait interactions with the soil environment and therefore to accurately forecast the potential C sequestration benefits of root breeding under different climatic and soil type conditions. We have developed the MEMS 2.0 ecosystem biogeochemical model to improve quantification of farm-scale soil carbon and greenhouse gas emissions. The new knowledge and large datasets produced by this project will be used to develop and drive an innovative model capable of forecasting the impacts on soil C stocks and nutrient dynamics. An innovation was to use the empirical data from the field studies (in 1, above) to model genetic variation in nitrogen use efficiencies and soil C input. Our work demonstrated that maize root-derived C rapidly replaces existing soil C and after 3 years of continuous maize, up to 20% of soil organic C in the topsoil (0-15cm) and 3% in the subsoil (15-30cm) was contributed by maize. However, this contribution did not entirely represent a net increase. Root C contribution to soil was affected by maize genetics. We have analyzed soils derived from the CSU field trials for C and N stocks, in the different soil physical fractions represented by the MEMS model, using both physical fractionation with elemental analyses, and Fourier transformed infrared spectroscopy. Data will be used to link crop nitrogen use efficiencies with soil C sequestration and provide data to bridge the field trials with the model development, for verification of model predictions. The project had a number of successful outcomes: we have used the new phenotyping platform to identify new genetic loci that can enhance root phenotypes; we have partnered with multiple maize seed companies phenotype varieties in their breeding programs; we have developed the MEMS model that can help inform industry on the potential for carbon sequestration in the agricultural sector, and which is now available at the CSU Soil Carbon Solutions Center for use.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

A Computer Model to Study the Response of Energetic Materials to a Range of Dynamic Loads

Over the past decade we developed a model to enable computer simulation of the mechanical and subsequent energetic response of explosives and propellants to mechanical insults such as impacts, perforations, drops, and falls. The model is embedded in computer simulation programs that solve the non-linear, large deformation equations of compressible solid and fluid flow in space and time. It is implemented as a user-defined model, which returns the updated stress tensor and composition that result from the simulation supplied strain tensor change. Although it is multi-phase, in that gas and solid species are present, it is single-velocity, in that the gas does not flow through the porous solid. More than 70 time-dependent variables are made available for additional analyses and plotting. The model encompasses a broad range of possible responses: mechanical damage with no energetic response, and a continuous spectrum of degrees of violence including delayed and prompt detonation. This work describes the basic workings of the model.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Electrical properties and conduction mechanism study by OLPT model of NaZnPO4 compound

Highlights: • The crystal structure was resolved using Fullproof program. • The conduction in NaZn PO{sub 4} is insured by OLPT model. • Ac conductivity of NaZn PO{sub 4} compound obeys the Joncher’s law. - Abstract: A polycrystalline sample with NaZnPO{sub 4} stoichiometry was synthesized by the conventional solid-state reaction and then identified and characterized by X-ray powder diffraction, Raman spectroscopy and impedance spectroscopy. The X-ray diffraction pattern revealed that the composite represents a single phase that crystallizes in the monoclinic system with a P2{sub 1}/n space group. All vibration modes of tetrahedral PO{sub 4} appeared in the Raman spectrum. Besides, the electrical conductivity behavior of the title compound was analysed as a function of frequency ranging from 209 Hz to 1 MHz and at a temperature interval ranging from 578 K to 728 K by means of impedance spectroscopy to elucidate the conduction mechanism in this compound. The temperature dependence of frequency exponent ′s′ showed that the conduction in NaZnPO{sub 4} is insured by the overlapping large polaron tunneling (OLPT) model. A correlation between electrical and structural properties was also depicted.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Theory, Solution Methods, and Implementation of the HERMES Model

The HERMES (high explosive response to mechanical stimulus) model was developed over the past decade to enable computer simulation of the mechanical and subsequent energetic response of explosives and propellants to mechanical insults such as impacts, perforations, drops, and falls. The model is embedded in computer simulation programs that solve the non-linear, large deformation equations of compressible solid and fluid flow in space and time. It is implemented as a user-defined model, which returns the updated stress tensor and composition that result from the simulation supplied strain tensor change. Although it is multi-phase, in that gas and solid species are present, it is single-velocity, in that the gas does not flow through the porous solid. More than 70 time-dependent variables are made available for additional analyses and plotting. The model encompasses a broad range of possible responses: mechanical damage with no energetic response, and a continuous spectrum of degrees of violence including delayed and prompt detonation. This paper describes the basic workings of the model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Models and Algorithms for Equilibrium Analysis of Mixed-Material Nucleic Acid Systems

Dynamic programming algorithms within the NUPACK software suite enable analysis of equilibrium base-pairing properties for complex and test tube ensembles containing arbitrary numbers of interacting nucleic acid strands. Currently, calculations are limited to single-material systems that are either all-RNA or all-DNA. Here, to enable analysis of mixed-material systems that are critical for modern applications in vitro, in situ, and in vivo, we develop physical models and dynamic programming algorithms that allow the material of the system to be specified at nucleotide resolution. Free energy parameter sets are constructed for both RNA/DNA and RNA/2'OMe-RNA mixed-material systems by combining available empirical mixed-material parameters with single-material parameter sets to enable treatment of the full complex and test tube ensembles. New dynamic programming recursions account for the material of each nucleotide throughout the recursive process. For a complex with N nucleotides, the mixed-material dynamic programming algorithms maintain the O(N 3 ) time complexity of the single-material algorithms, enabling efficient calculation of diverse physical quantities over complex and test tube ensembles (e.g., complex partition function, equilibrium complex concentrations, equilibrium base-pairing probabilities, minimum free energy secondary structure(s), and Boltzmann-sampled secondary structures) at a cost increase of roughly 2.0-3.5×. The results of existing single-material algorithms are exactly reproduced when applying the new mixed-material algorithms to single-material systems. Accuracy is significantly enhanced using mixed-material models and algorithms to predict RNA/DNA and RNA/2'OMe-RNA duplex melting temperatures from the experimental literature as well as RNA/DNA melt profiles from new experiments. In conclusion, mixed-material analyses can be performed online using the NUPACK web app (www.nupack.org) or locally using the NUPACK Python module.

2′OMe-RNA↗
DOE OSTI2016

Digital Architecture Planning Model

As part of the U.S. Department of Energy’s Light Water Reactor Sustainability Program, the Digital Architecture (DA) Project focuses on providing a model that nuclear utilities can refer to when planning deployment of advanced technologies. The digital architecture planning model (DAPM) is the methodology for mapping power plant operational and support activities into a DA that unifies all data sources needed by the utilities to operate their plants. The DA is defined as a collection of information technology capabilities needed to support and integrate a wide spectrum of real-time digital capabilities for performance improvements of nuclear power plants. DA can be thought of as integration of the separate instrumentation and control and information systems already in place in nuclear power plants, which are brought together for the purpose of creating new levels of automation in plant work activities. A major objective in DAPM development was to survey all key areas that needed to be reviewed in order for a utility to make knowledgeable decisions regarding needs and plans to implement a DA at the plant. The development was done in two steps. First, researchers surveyed the nuclear industry in order to learn their near-term plans for adopting new advanced capabilities and implementing a network (i.e., wireless and wire) infrastructure throughout the plant, including the power block. Secondly, a literature review covering regulatory documents, industry standards, and technical research reports and articles was conducted. The objective of the review was to identify key areas to be covered by the DAPM, which included the following: 1. The need for a DA and its benefits to the plant 2. Resources required to implement the DA 3. Challenges that need to be addressed and resolved to implement the DA 4. Roles and responsibilities of the DA implementation plan. The DAPM was developed based on results from the survey and the literature review. Model development, including the survey results and conclusions made about the key areas during the literature review, are described in this report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Technical Report on Waveform Fit Metrics for Global Models

The new WAVEFORMS Initiative in the Ground-based Nuclear Detonation Detection (GNDD) program includes an increased emphasis on the development of Earth models and methods to predict entire seismic and acoustic waveforms more accurately. In general, this increased emphasis is predicated on the need to better characterize seismic events and provide improved model-based discrimination between event types including earthquakes and explosions. More specifically, while current moment tensor inversion methods tend to work well for larger events (M>~4) using tuned 1-D Earth models, the development of state-of-the-art 3-D models and methods is required for the prediction of shorter period waves over large areas for discrimination of smaller events. There is no standard metric for model-based waveform prediction accuracy used in the waveform modeling/inversion community. However, there are several popular waveform misfit definitions; and minimizing the corresponding objective functions is the goal of waveform inversion. Some example misfit definitions employed for adjoint waveform tomography include measures of simple travel time differences (e.g. Tape et al., 2010), cross-correlation travel time differences (e.g. Luo and Schuster, 1991), multi-taper frequency dependent methods (e.g. Lei et al., 2020), time-frequency phase misfit functions (e.g. Fichtner 2010; Rodgers et al., 2022), normalized cross-correlation methods (e.g. Tao et al., 2018), and others. In some cases, these misfit definitions also involve complicated weighting schemes and summations over multiple frequency bands making it difficult to duplicate the misfit measurement with alternative models and datasets. Although each of the misfit definitions mentioned above are useful for developing waveform models, the actual misfit values are not usually meaningful outside of a given project, model, and/or dataset. Therefore, it is difficult to understand and communicate model performance for predicting waveforms and comparing to other models and/or new model iterations with a different dataset. Therefore, there is a need for a generalized method for evaluating overall model performance that is independent from the specific misfit chosen to develop the waveform models that is also intuitive and meaningful. In this report, we describe a new metric we refer to as ‘Percent of Correlated Signal’. The following sections describe and demonstrate the metric with a case study event and a more rigorous test using a random selection of globally distributed events. While the focus here is on global tomography models, the metric is meant to applicable to regional ‘wiggle-for-wiggle’ waveform models/studies as well.

58 GEOSCIENCES↗
DOE OSTI2017

Relaxation of the composite Higgs little hierarchy

We describe a composite Higgs scenario in which a cosmological relaxation mechanism naturally gives rise to a hierarchy between the weak scale and the scale of spontaneous global symmetry breaking. This is achieved through the scanning of sources of explicit global symmetry breaking by a relaxion field during an exponentially long period of inflation in the early universe. We explore this mechanism in detail in a specific composite Higgs scenario with QCD-like dynamics, based on an ultraviolet SU(N )TC ‘technicolor’ confining gauge theory with three Dirac technifermion flavors. We find that we can successfully generate a hierarchy of scales ξ≡ 2 /F π 2 ≳1.2×10 –4 (i.e., compositeness scales F π ~ 20 TeV) without tuning. This evades all current electroweak precision bounds on our (custodial violating) model. While directly observing the heavy composite states in this model will be challenging, a future electroweak precision measurement program can probe most of the natural parameter space for the model. We also highlight signatures of more general composite Higgs models in the cosmological relaxation framework, including some implications for flavor and dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Bridging the gap between sustainable technology adoption and protecting natural resources: Predicting intentions to adopt energy management technologies in California

To achieve energy savings, emerging energy management technologies and programs require customer adoption. Although a variety of models can be used to explain the adoption of energy management technologies and programs, they overlook the seemingly unconventional element of level of affiliation with nature. In fact, connectedness to nature has been identified as an important driver of many pro-environmental behaviors, but its role in pro-environmental technology adoption is also not well understood. Can affiliation with nature help to bridge the apparent gap—and complex chain of events—between sustainable technology adoption and protecting natural resources? Based on survey data from 856 southern California residents, this study investigated the influence of connectedness to nature and other factors on intentions to adopt five energy management technologies and programs: using three platforms to monitor home energy use (website, mobile phone application, in-home display); signing up for a time-of-use pricing plan; and participating in demand response events. Regression results showed that nature connectedness was the strongest predictor of all outcomes such that higher nature connectedness predicted greater likelihood of technology and program adoption. In conclusion, these findings suggest that connectedness to nature may facilitate “bridging the logic gap” between sustainable innovation adoption and environmental protection.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

The allocation of a variable series reactor considering AC constraints and contingencies

The Variable Series Reactors (VSRs) can efficiently control the power flow through the adjustment of the line reactance. When they are appropriately allocated in the power network, the transmission congestion and generation cost can be reduced. Our work proposes a planning model to optimally allocate VSRs considering AC constraints and multi-scenarios including base case and contingencies. The planning model is originally a non-convex large scale mixed integer nonlinear program (MINLP), which is generally intractable. The proposed Benders approach decomposes the MINLP model into a mixed integer linear program (MILP) master problem and a number of nonlinear subproblems. Numerical case studies based on IEEE 118-bus demonstrate the high performance of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Block-structured, equal-workload, multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Total Variation Diminishing)

Abstract. We describe the development of a block-structured, equal-CPU-load (central processing unit), multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Fully Nonlinear Boussinesq Wave Model with Total Variation Diminishing Solver). The new model framework does not interfere with the core solver, and thus the core program, FUNWAVE-TVD, is still a standalone model used for a single grid. The nesting interface manages the time sequencing and two-way nesting processes between the parent grid and child grid with grid refinement in a hierarchical manner. Workload balance in the MPI-based (message passing interface) parallelization is handled by an equal-load scheme. A strategy of shared array allocation is applied for data management that allows for a large number of nested grids without creating additional memory allocations. Four model tests are conducted to verify the nesting algorithm with assessments of model accuracy and the robustness in the application in modeling transoceanic tsunamis and coastal effects.

Choi, Young-Kwang↗
DOE OSTI2018

Compiling Adiabatic Quantum Programs

We develop a non-cooperative game-theoretic model for the problem of graph minor-embedding to show that optimal compiling of adiabatic quantum programs in the sense of Nash equilibrium is possible.

Khan, Faisal Shah↗
DOE OSTI2020

Assessment of Precipitating Marine Stratocumulus Clouds in the E3SMv1 Atmosphere Model: A Case Study from the ARM MAGIC Field Campaign

This paper presents a process-oriented evaluation of precipitating stratocumulus and its transition to cumulus in version 1 of the Energy Exascale Earth System Model (E3SMv1) using comprehensive case-study observations from a field campaign of the Atmospheric Radiation Measurement program (ARM). The E3SMv1 single-column model (SCM) of the marine boundary layer and its low clouds and precipitation are compared to observations including subcloud drizzle retrievals from a combination of Doppler radar and lidar backscatter measurements. Additionally, the SCM is also compared to a large-eddy simulation (LES) of the same case. The combination of advanced remote sensing observations and LES is a powerful framework to evaluate the physical parameterizations of large-scale models. Given the observed large-scale environment, the E3SMv1 SCM realistically represents the evolution of clouds and boundary layer structure during the stratocumulus-to-cumulus transition. The model well simulates the liquid water path and its diurnal cycle in the stratocumulus period as well as the two-layer vertical thermodynamic structure and lower cloud fraction in the transition period. E3SMv1’s success in simulating the cloud in the stratocumulus period permitted examination of its precipitation processes. Here problems were identified with E3SMv1 producing an unrealistically small subcloud precipitation fraction, an unrealistic double peak in the vertical profiles of precipitation mass, and drizzle that evaporates too close to the surface. Further model diagnostics determined that these unrealistic characteristics resulted from an overly long microphysics time step and an unrealistic parameterization of the precipitation fraction. These results imply that careful consideration of these issues is needed in order to better simulate precipitation processes in marine stratocumulus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Construction of ground-state preserving sparse lattice models for predictive materials simulations

First-principles based cluster expansion models are the dominant approach in ab initio thermodynamics of crystalline mixtures enabling the prediction of phase diagrams and novel ground states. However, despite recent advances, the construction of accurate models still requires a careful and time-consuming manual parameter tuning process for ground-state preservation, since this property is not guaranteed by default. In this paper, we present a systematic and mathematically sound method to obtain cluster expansion models that are guaranteed to preserve the ground states of their reference data. The method builds on the recently introduced compressive sensing paradigm for cluster expansion and employs quadratic programming to impose constraints on the model parameters. The robustness of our methodology is illustrated for two lithium transition metal oxides with relevance for Li-ion battery cathodes, i.e., Li 2x Fe 2(1-x) O 2 and Li 2x Ti 2(1-x) O 2 , for which the construction of cluster expansion models with compressive sensing alone has proven to be challenging. We demonstrate that our method not only guarantees ground-state preservation on the set of reference structures used for the model construction, but also show that out-of-sample ground-state preservation up to relatively large supercell size is achievable through a rapidly converging iterative refinement. This method provides a general tool for building robust, compressed and constrained physical models with predictive power.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Systems and methods for enhanced power system model validation

A system for enhanced power system model validation is provided. The system includes a computing device including at least one processor in communication with at least one memory device. The at least one processor is programmed to store a plurality of models for a plurality of devices and a plurality of input files associated with the plurality of models, receive, from a user, a selection of model of the plurality of models to simulate, retrieve one or more input files of the plurality of input files, perform a model validity check on the selected model, if the selected model passed the model validity check, perform a model calibration on the selected model, and if the selected model passed the model calibration, perform a post evaluation on the selected model.

Wang, Honggang↗
DOE OSTI2018

Microstructure Characterization and Modeling for Improved Electrode Design

As part of DOE's Computer-Aided Engineering of Batteries Program, the National Renewable Energy Laboratory is developing detailed models capturing the influence of lithium-ion battery electrode design, recipe and processing on the electrode's microstructure and relating that microstructure to device-level performance. Given the difficulty in obtaining 3D microstructural images of the electrode's inert components, team member Purdue University developed an algorithm to computationally generate the so-called carbon-binder domain (CBD) for any given recipe. Mesoscale models explore the device-level impact of the CBD phase on multiple idealized and actual electrode geometries. With the inclusion of this CBD phase, microstructure models are used to predict the tortuosity of 14 different graphite and NMC electrode designs. Tortuosity predictions are shown in good agreement with experimental direct measurement and electrochemical rate studies.

25 ENERGY STORAGE↗

Refine your search to explore more results.