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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Integration of Multiple Real-time Simulation Platforms with AIO for Scalability

This paper introduces a practical and scalable approach to extend interoperability of Controller Hardware in the Loop (CHIL) validations for large scale microgrids, networked microgrids, and power electronics-based feeders. The work focuses on integrating multiple real-time simulators using Analog Input/Output (AIO) interface techniques in heterogeneous CHIL environment. It explores interfacing methods, highlighting key challenges related to dynamic accuracy and maintaining bidirectional power balance. A comparative evaluation of the Ideal Transformer Method is presented, assessing its effectiveness in multi-CHIL integration scenarios. The feasibility of this setup is demonstrated through a real-time use case involving multiple Typhoon HIL and Opal-RT platforms, showcasing its applicability for distributed system studies.

Khalid, Mohammad [ORNL] (ORCID:0000000179208805)↗
DOE OSTI2016

Liquid Secondary Waste Grout Formulation and Waste Form Qualification

This report describes the results from liquid secondary waste (LSW) grout formulation and waste form qualification tests performed at Pacific Northwest National Laboratory (PNNL) for Washington River Protection Solutions (WRPS) to evaluate new formulations for preparing a grout waste form with high-sulfate secondary waste simulants and the release of key constituents from these grout monoliths. Specific objectives of the LSW grout formulation and waste form qualification tests described in this report focused on five activities: 1.preparing new formulations for the LSW grout waste form with high-sulfate LSW simulants and solid characterization of the cured LSW grout waste form; 2.conducting the U.S. Environmental Protection Agency (EPA) Method 1313 leach test (EPA 2012) on the grout prepared with the new formulations, which solidify sulfate-rich Hanford Tank Waste Treatment and Immobilization Plant (WTP) off-gas condensate secondary waste simulant, using deionized water (DIW); 3.conducting the EPA Method 1315 leach tests (EPA 2013) on the grout monoliths made with the new dry blend formulations and three LSW simulants (242-A evaporator condensate, Environmental Restoration Disposal Facility (ERDF) leachate, and WTP off-gas condensate) using two leachants, DIW and simulated Hanford Integrated Disposal Facility (IDF) Site vadose zone pore water (VZPW); 4.estimating the 99 Tc desorption K d (distribution coefficient) values for 99 Tc transport in oxidizing conditions to support the IDF performance assessment (PA); 5.estimating the solubility of 99 Tc(IV)-bearing solid phases for 99 Tc transport in reducing conditions to support the IDF PA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Incorporating social impact on new product adoption in choice modeing: A case study in green vehicles

While discrete choice analysis is prevalent in capturing consumer preferences and describing their choice behaviors in product design, the traditional choice modeling approach assumes that each individual makes independent decisions, without considering the social impact. However, empirical studies show that choice is social - influenced by many factors beyond engineering performance of a product and consumer attributes. To alleviate this limitation, we propose a new choice modeling framework to capture the dynamic influence from social networks on consumer adoption of new products. By introducing social influence attributes into a choice utility function, social network simulation is integrated with the traditional discrete choice analysis in a three-stage process. Our study shows the need for considering social impact in forecasting new product adoption. Using hybrid electric vehicles as an example, our work illustrates the procedure of social network construction, social influence evaluation, and choice model estimation based on data from the National Household Travel Survey. Our study also demonstrates several interesting findings on the dynamic nature of new technology adoption and how social networks may influence hybrid electric vehicle adoption. (C) 2014 Elsevier Ltd. All rights reserved

Discrete choice analysis↗
DOE OSTI2019

Evaluating Thermal Corrections for Adsorption Processes at the Metal/Gas Interface

Adsorption and desorption steps are key for active catalysts and rely on a subtle balance between enthalpic and entropic terms. Although the enthalpic term is becoming ever more accurate through density functional development, the entropic term remains underrated and its precise determination a great challenge. In this work, we have performed extensive first principles thermodynamic integration (TI) simulations for the adsorption of small (e.g., CO) to larger (e.g., phenol) molecules at metallic surfaces and compared their adsorption free energies to the values obtained by vertical, static statistical mechanics approximations to thermal corrections invoking three different approximations for the low-frequency modes. We have found an excellent agreement between the vertical corrections and the TI for minima, for both weakly bound systems (e.g. CO 2 and formic acid) and strongly chemisorbed molecules such as phenol or CO. While the treatment of the low-frequency modes has a minor impact on the agreement with TI, all vertical corrections systematically overestimate activation energies by 0.1-0.2 eV compared to TI, demonstrating a noticeable lowering of activation barriers. As an effect of this study, we suggest that the vertical corrections and in particular the standard harmonic approximation can be safely applied to chemisorption minima, while the activation energies are likely to be overestimated. Hence, if a greater accuracy than ~0.2 eV is required for activation free energies, we recommend to use thermodynamic integration, which for small to medium-sized molecules in gas phase is accessible with a reasonable computational effort, but requires a dense sampling in the transition state region.

Réocreux, Romain↗
DOE OSTI2016

Logical design of anti-prion agents using NAGARA

To accelerate the logical drug design procedure, we created the program “NAGARA,” a plugin for PyMOL, and applied it to the discovery of small compounds called medical chaperones (MCs) that stabilize the cellular form of a prion protein (PrP{sup C}). In NAGARA, we constructed a single platform to unify the docking simulation (DS), free energy calculation by molecular dynamics (MD) simulation, and interfragment interaction energy (IFIE) calculation by quantum chemistry (QC) calculation. NAGARA also enables large-scale parallel computing via a convenient graphical user interface. Here, we demonstrated its performance and its broad applicability from drug discovery to lead optimization with full compatibility with various experimental methods including Western blotting (WB) analysis, surface plasmon resonance (SPR), and nuclear magnetic resonance (NMR) measurements. Combining DS and WB, we discovered anti-prion activities for two compounds and tegobuvir (TGV), a non-nucleoside non-structural protein NS5B polymerase inhibitor showing activity against hepatitis C virus genotype 1. Binding profiles predicted by MD and QC are consistent with those obtained by SPR and NMR. Free energy analyses showed that these compounds stabilize the PrP{sup C} conformation by decreasing the conformational fluctuation of the PrP{sup C}. Because TGV has been already approved as a medicine, its extension to prion diseases is straightforward. Finally, we evaluated the affinities of the fragmented regions of TGV using QC and found a clue for its further optimization. By repeating WB, MD, and QC recursively, we were able to obtain the optimum lead structure. - Highlights: • NAGARA integrates docking simulation, molecular dynamics, and quantum chemistry. • We found many compounds, e.g., tegobuvir (TGV), that exhibit anti-prion activities. • We obtained insights into the action mechanism of TGV as a medical chaperone. • Using QC, we obtained useful information for optimization of the lead compound, TGV. • NAGARA is a convenient platform for drug discovery and lead optimization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

ID201202961, DOE S-124,539, Information Security Analysis Using Game Theory and Simulation

Information security analysis can be performed using game theory implemented in dynamic simulations of Agent Based Models (ABMs). Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. Our approach addresses imperfect information and scalability that allows us to also address previous limitations of current stochastic game models. Such models only consider perfect information assuming that the defender is always able to detect attacks; assuming that the state transition probabilities are fixed before the game assuming that the players actions are always synchronous; and that most models are not scalable with the size and complexity of systems under consideration. Our use of ABMs yields results of selected experiments that demonstrate our proposed approach and provides a quantitative measure for realistic information systems and their related security scenarios.

Availablity↗
DOE OSTI2015

Path integral molecular dynamics within the grand canonical-like adaptive resolution technique: Simulation of liquid water

Quantum effects due to the spatial delocalization of light atoms are treated in molecular simulation via the path integral technique. Among several methods, Path Integral (PI) Molecular Dynamics (MD) is nowadays a powerful tool to investigate properties induced by spatial delocalization of atoms; however, computationally this technique is very demanding. The above mentioned limitation implies the restriction of PIMD applications to relatively small systems and short time scales. One of the possible solutions to overcome size and time limitation is to introduce PIMD algorithms into the Adaptive Resolution Simulation Scheme (AdResS). AdResS requires a relatively small region treated at path integral level and embeds it into a large molecular reservoir consisting of generic spherical coarse grained molecules. It was previously shown that the realization of the idea above, at a simple level, produced reasonable results for toy systems or simple/test systems like liquid parahydrogen. Encouraged by previous results, in this paper, we show the simulation of liquid water at room conditions where AdResS, in its latest and more accurate Grand-Canonical-like version (GC-AdResS), is merged with two of the most relevant PIMD techniques available in the literature. The comparison of our results with those reported in the literature and/or with those obtained from full PIMD simulations shows a highly satisfactory agreement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Integrating in situ TEM experiments and atomistic simulations for defect mechanics

With recent advances in computational modeling and in situ transmission electron microscopy (TEM) technologies, there have been increased efforts to apply these approaches to understand defect-based mechanisms dictating deformation mechanics. In situ TEM experiments and atomistic simulations each have their own unique limitations, including observable length and time scales and accessibility of information, motivating approaches that combine the two approaches. In this paper, we review recent studies that combine atomistic simulations and in situ TEM experiments to understand defect mechanisms associated with deformation of metals and alloys. In addition, we discuss ongoing developments in characterization and simulation capabilities that are expected to significantly advance the field of defect mechanics and allow greater integration between atomistic simulations and in situ TEM experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Pathways of sulfate enhancement by natural and anthropogenic mineral aerosols in China

China, the world’s largest consumer of coal, emits approximately 30 million tons of sulfur dioxide (SO₂) per year. SO₂ is subsequently oxidized to sulfate in the atmosphere. However, large gaps exist between model-predicted and measured sulfate levels in China. Long-term field observations and numerical simulations were integrated to investigate the effect of mineral aerosols on sulfate formation. We found that mineral aerosols contributed a nationwide average of approximately 22% to sulfate production in 2006. The increased sulfate concentration was approximately 2 μg m⁻³ in the entire China. In East China and the Sichuan Basin, the increments reached 6.3 μg m⁻³ and 7.3 μg m⁻³, respectively. Mineral aerosols led to faster SO₂ oxidation through three pathways. First, more SO₂ was dissolved as cloud water alkalinity increased due to water-soluble mineral cations. Sulfate production was then enhanced through the aqueous-phase oxidation of S(IV) (dissolved sulfur in oxidation state +4). The contribution to the national sulfate production was 5%. Second, sulfate was enhanced through S(IV) catalyzed oxidation by transition metals. The contribution to the annual sulfate production was 8%, with 19% during the winter that decreased to 2% during the summer. Third, SO₂ reacts on the surface of mineral aerosols to produce sulfate. The contribution to the national average sulfate concentration was 9% with 16% during the winter and a negligible effect during the summer. The inclusion of mineral aerosols does resolve model discrepancies with sulfate observations in China, especially during the winter. These three pathways, which are not fully considered in most current chemistry-climate models, will significantly impact assessments regarding the effects of aerosol on climate change in China.

Huang, Xin↗
DOE OSTI2019

Nonlinear Fluctuating Hydrodynamics for the Classical XXZ Spin Chain

Using the framework of nonlinear fluctuating hydrodynamics (NFH), we examine equilibrium spatio-temporal correlations in classical ferromagnetic spin chains with nearest neighbor interactions. In particular, we consider the classical XXZ-Heisenberg spin chain (also known as Lattice Landau–Lifshitz or LLL model) evolving deterministically and chaotically via Hamiltonian dynamics, for which energy and z-magnetization are the only locally conserved fields. For the easy-plane case, this system has a low-temperature regime in which the difference between neighboring spin’s angular orientations in the XY plane is an almost conserved field. According to the predictions of NFH, the dynamic correlations in this regime exhibit a heat peak and propagating sound peaks, all with anomalous broadening. We present a detailed molecular dynamics test of these predictions and find a reasonably accurate verification. Additionally, we find that, in a suitable intermediate temperature regime, the system shows two sound peaks with Kardar-Parisi-Zhang (KPZ) scaling and a heat peak where the expected anomalous broadening is less clear. In high temperature regimes of both easy plane and easy axis case of LLL, our numerics show clear diffusive spin and energy peaks and absence of any sound modes, as one would expect. We also simulate an integrable version of the XXZ-model, for which the ballistic component instead moves with a broad range of speeds rather than being concentrated in narrower peaks around the sound speed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Bioalcohol production from acidogenic products via a two-step process: A case study of butyric acid to butanol

This article presents the full study (lab-scale experimental study and large-scale techno-economic analysis) results of a two-step catalytic process for the conversion of organic waste–derived butyric acid to butanol. Butanol from biomass resources like organic waste promise to become an attractive and sustainable fuel and industrial precursor due to an increase in greenhouse gas content in the atmosphere. Therefore, research in this field is important for energy applications and reduction in greenhouse gas emissions. In this regard, a two-step process was applied in this study to produce butanol from butyric acid that can potentially be derived from organic waste. The two-step process consists of the (1) esterification of butyric acid to methyl butyrate and (2) hydrogenolysis of this methyl butyrate to butanol. The first reaction, esterification of butyric acid, was optimized using carbon-based catalysts. The production of butanol from methyl butyrate via hydrogenolysis was investigated using bimetallic Pt–Co catalysts. The hydrogenolysis of methyl butyrate on these catalysts under optimal conditions of 250 °C, 5 MPa H 2 , and a feed/catalyst weight ratio of 11.2 led to 54.1% selectivity toward 1-butanol. Based on the experimental results, an integrated process simulation model was developed to determine the economic potential of the two-step production of butanol from butyric acid. Using this model, the techno-economic feasibility of the two-step process was analyzed. Here, the minimum selling price (MSP) of 1-butanol produced from butyric acid using this process was US dollars 3.388 per gallon of gasoline equivalent (GGE). This MSP is in the range of recent biofuel market prices of US dollars 2.03/GGE to US dollars 3.83/GGE.

09 BIOMASS FUELS↗
DOE OSTI2025

Broad range material-to-system screening of metal–organic frameworks for hydrogen storage using machine learning

Hydrogen is pivotal in the transition to sustainable energy systems, playing major roles in power generation and industrial applications. Metal–organic frameworks (MOFs) have emerged as promising mediums for efficient hydrogen storage. However, identifying potential candidates for deployment is challenging due to the vast number of currently available synthesized MOFs. This study integrates molecular simulations, machine learning, and techno-economic analysis to evaluate the performance of MOFs across broad operation conditions for hydrogen storage applications. While previous screenings of MOF databases have predominantly emphasized high hydrogen capacities under cryogenic conditions, this study reveals that optimal temperatures and pressures for cost minimization depend on the raw price of the MOF. Specifically, when MOFs are priced at $15/kg, among the 9720 MOFs tested, 9692 MOFs achieve the lowest cost at temperatures between 170 K and 250 K and a pressure of 150 bar. Under these optimal conditions, 362 MOFs deliver a lower levelized cost of storage than 350 bar compressed gas hydrogen storage. Furthermore, this study reveals key material properties that result in low system cost, such as high surface areas (>3000 m2/g), large void fractions (>0.78), and large pore volumes (>1.1 cm3/g).

Hydrogen storage↗
DOE OSTI2021

Unlocking the secret of lignin-enzyme interactions: Recent advances in developing state-of-the-art analytical techniques

Bioconversion of renewable lignocellulosics to produce liquid fuels and chemicals is one of the most effective ways to solve the problem of fossil resource shortage, energy security, and environmental challenges. Among the many biorefinery pathways, hydrolysis of lignocellulosics to fermentable monosaccharides by cellulase is arguably the most critical step of lignocellulose bioconversion. In the process of enzymatic hydrolysis, the direct physical contact between enzymes and cellulose is an essential prerequisite for the hydrolysis to occur. However, lignin is considered one of the most recalcitrant factors hindering the accessibility of cellulose by binding to cellulase unproductively, which reduces the saccharification rate and yield of sugars. This results in high costs for the saccharification of carbohydrates. The various interactions between enzymes and lignin have been explored from different perspectives in literature, and a basic lignin inhibition mechanism has been proposed. However, the exact interaction between lignin and enzyme as well as the recently reported promotion of some types of lignin on enzymatic hydrolysis is still unclear at the molecular level. Multiple analytical techniques have been developed, and fully unlocking the secret of lignin-enzyme interactions would require a continuous improvement of the currently available analytical techniques. This review summarizes the current commonly used advanced research analytical techniques for investigating the interaction between lignin and enzyme, including quartz crystal microbalance with dissipation (QCM-D), surface plasmon resonance (SPR), attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, atomic force microscopy (AFM), nuclear magnetic resonance (NMR) spectroscopy, fluorescence spectroscopy (FLS), and molecular dynamics (MD) simulations. Interdisciplinary integration of these analytical methods is pursued to provide new insight into the interactions between lignin and enzymes. Finally, this review will serve as a resource for future research seeking to develop new methodologies for a better understanding of the basic mechanism of lignin-enzyme binding during the critical hydrolysis process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Shape optimization under uncertainty for rotor blades of horizontal axis wind turbines

We present a computational framework for the shape optimization of a Horizontal-Axis Wind Turbine (HAWT) rotor blade under uncertainty. Our framework integrates aerodynamic simulations based on the blade element method which utilizes reduced order models of the blade structure and wind load with design sensitivity analysis and nonlinear programming. The wind velocity is modeled as a stochastic process to account for variations in time and space. An additional stochastic process accounts for uncertainties in the structural material properties. The uncertainty propagation is based on a non-intrusive polynomial chaos expansion that allows accurate estimation of stochastic performance metrics such as generated power and structural compliance. Sensitivities of cost and constraint functions with respect to shape parameters namely twist angles are computed with an efficient scheme to enable gradient based optimization. To demonstrate the effect of uncertainty, designs obtained from optimization under uncertainty are compared to those obtained from deterministic optimization.

42 ENGINEERING↗
DOE OSTI2023

Optimizing mixed cool thermal storage systems across a connected community

A high level of electric demand flexibility must be integrated into our building infrastructure to enable greater renewable energy penetration in the grid. In the U.S., 9% of electricity generated is used to cool buildings in a periodic manner, making this end-use an ideal target for active management through cool thermal energy storage (CTES) technologies. Historic uses for CTES are designed around central chilled water plants, but these systems cool less than 25% of U.S. commercial floorspace. Emerging technologies are under development to serve the many smaller distributed cooling systems, such as rooftop units (RTUs), and have the potential to add CTES to an additional 66% of cooled commercial floorspace. However, these unitary thermal storage systems (UTSS) lack the modeling and analysis tools to evaluate them in the future interactive grid context. Here, this study develops the modeling and optimization tools necessary to simultaneously examine central and distributed ice storage systems within the multi-building, connected community context. An integrated simulation-optimization workflow is created to allow for rapid customized analysis. Results demonstrate the energy and flexibility tradeoffs of various implementations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8) for advanced open-source tritium transport and fuel cycle modeling

Tritium management is critical for the safety, sustainability, and economics of fusion energy systems, and advanced and reliable modeling tools help accelerate the development of tritium technologies. This paper presents the Tritium Migration Analysis Program, Version 8 (TMAP8), an open-source, MOOSE-based application developed to provide state-of-the-art tritium transport and fuel cycle modeling capabilities. TMAP8 aims to expand the capabilities of previous versions (i.e., TMAP4 and TMAP7) by leveraging modern computational techniques, ensuring high software quality assurance standards (key to building trust), and enabling multispecies, multiscale, and multiphysics simulations for integrated tritium transport modeling in complex geometries. This paper outlines TMAP8’s scope and rigorous development practices, emphasizing its transparency, accessibility, modularity, and reliability. We present the current suite of verification and validation cases based on those from TMAP4, demonstrating TMAP8’s accuracy and reliability against analytical solutions and experimental data. Additionally, the paper showcases TMAP8’s integrated fuel cycle modeling capabilities, highlighting its applicability at various scales and levels. The TMAP8 code and documentation are openly available, promoting collaborative development and widespread adoption within the fusion community. Future work will soon expand TMAP8’s verification and validation suite to include those from TMAP7 and other recent experimental studies for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Molecular insights into Yb(III) speciation in sulfate-bearing hydrothermal fluids from X-ray absorption spectra informed by ab initio molecular dynamics

Rare earth elements (REEs) are critical for advanced technologies, yet in hydrothermal aqueous solutions the molecular level details of their interaction with ligands that control their geochemical transport and deposition remain poorly understood. Here, this study elucidates the coordination behavior of Yb 3+ in sulfate-rich hydrothermal fluids using in situ extended X-ray absorption fine structure (EXAFS) spectroscopy and ab initio molecular dynamics (AIMD) simulations. By integrating multi-angle EXAFS with AIMD-derived constraints, we precisely resolve Yb 3+ coordination structures and ligand interactions under hydrothermal conditions. At room temperature, Yb 3+ is coordinated by five water molecules and two sulfate ligands (coordination number, CN = 8), forming a distorted square antiprism geometry. Increasing temperature induces progressive dehydration, reducing the hydration shell and favoring stronger sulfate complexation. At 200°C, sulfate ligands reorganize around Yb 3+ , shifting its geometry to a capped octahedron (CN = 7). At 300 °C, sulfate binding dominates, leading to structural reorganization that parallels the onset of sulfate mineral precipitation, consistent with the retrograde solubility of REE sulfates. These findings provide direct molecular-scale evidence that sulfate acts as both a transport and deposition ligand, critically influencing REE mobility in geochemical environments. Our results can also help to refine thermodynamic models of REE speciation in high-temperature hydrothermal fluids and improve our understanding of REE ore formation processes in nature.

AIMD↗