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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 OSTI2026

Scaling dynamics in low-salt-rejection reverse osmosis for high-salinity produced water desalination: Mechanistic modeling and membrane autopsy

Membrane scaling remains a critical barrier to the reliable operation of desalination systems, particularly for hypersaline produced water (PW) treatment. This study fills the knowledge gap of autopsy-based model validation for PW desalination by elucidating scaling mechanisms in a Low-Salt-Rejection Reverse Osmosis (LSRRO) system through the integration of pilot-scale experimentation and complementary modeling approaches. A semi-empirical modeling framework was developed and applied to a multistage pilot LSRRO system equipped with nanofiltration and RO membranes treating high-salinity PW from the Permian Basin. Water quality analysis showed that total dissolved solids decreased from ~130,000 mg/L to ~1900 mg/L in the permeate, then further reduced to ~300 mg/L by a second-pass RO. Two different thermodynamic modeling approaches were evaluated: the first extends the LSRRO framework by incorporating system complexity and scaling phenomena, whereas the second method explicitly captures concentration polarization in localized supersaturation. Both methods illustrate the tendency for carbonate and sulfate scaling throughout the stages. Membrane autopsies revealed a silica-dominated deposit matrix, localized CaSO 4 at Stage 2, and minor barite/celestite despite their prominence in model predictions. Quantum-chemical calculations indicated silica scaling can be rationalized by favorable adsorption of H 4 SiO 4 on Fe-oxide surfaces (ΔG ≈ −44 kJ/mol), providing a kinetic pathway for interfacial inorganic polymerization even when bulk equilibrium predictions are conservative. Overall, the thermodynamic scaling modeling and membrane autopsy revealed heterogeneous, localized deposits with limited impact on LSRRO performance, while quantum analysis rationalized the thermodynamically unfavorable precipitation formation under bulk equilibrium, reconciling model–autopsy discrepancies. These insights support targeted pretreatment and silica-specific antiscalants to extend membrane lifetime and increase recovery, providing a transferable framework for hypersaline water desalination systems. The combined experimental–computational approach provides new mechanistic insight into scaling in hypersaline membrane systems and establishes a transferable framework for predicting and mitigating scaling in next-generation desalination technologies.

Low-salt-rejection reverse osmosis↗
DOE OSTI2024

Stochastic Maxwell-Bloch equations for modeling amplified spontaneous emission

An approach for studying atom-radiation interaction has been developed, associating quantum operators with stochastic variables governed by discrete Heisenberg equations. This framework models general multilevel atomic systems using the paraxial approximation in both single- and multipass configurations. Simulation results for x-ray laser oscillators with parameters of interest are presented. Finally, the stochastic model is efficient to solve, as the required computational resources scale linearly with the number of emitters, and it may be applicable to various other quantum systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Characterizing in-stream turbulent flow for tidal energy converter siting in Cook Inlet, Alaska

Cook Inlet in Alaska is the most promising location for tidal energy development in the U.S. due to its significant tidal range of approximately 10 meters and high volume flux. The inlet's unique geometry and flow characteristics make it the most energetic tidal stream in the nation, with GW-scale potential energy capacity. With the growing interest in tidal energy converter (TEC) deployment in this area, we implemented a regional-scale, 3D hydrodynamic modeling framework to predict tidal current and turbulence characteristics that can assist TEC designers and project managers. We validated the model results extensively using various datasets collected with bottom-mounted acoustic Doppler current profilers and velocimeters. The comparison between the model outputs and observational data highlighted the effectiveness of the 3D FVCOM model and the Mellor-Yamada Level 2.5 Turbulence Model in accurately assessing macro-scale kinetic energy, turbulence intensity, and the production and dissipation rates at a prospective TEC site. Using two months of model simulation data, we examined the channel cross-section for TEC deployment, focusing on undisturbed power density and macro-scale turbulent properties. Further, our findings indicate that understanding the turbulence characteristics and flow properties can enhance Stage I/II resource characterization by identifying optimal locations for TECs and their layouts within the channel. Furthermore, we demonstrated that TEC designers can utilize macro-scale turbulence data from 3D coastal models as boundary conditions for other turbulence models, allowing for a more detailed resolution of the turbulence structure at TEC siting locations. Ultimately, this work emphasizes the importance of estimating flow and turbulence conditions in energetic systems to understand turbulent sites better and improve resource characterization.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Modeling of the spray-induced wall stress acting on the ignition assistance device

This research introduces a novel wall-stress model called the Spray-Induced Wall Stress (SIWS) model, which considers the effects of spray-wall impingement and the resulting formation of wall stress within the Lagrangian spray modeling framework. The primary objective of this paper is to provide a mathematical description of the fundamental physics underlying the model. Subsequently, the proposed model is validated using existing experimental data. Here, the remainder of the study focuses on the practical application of the model to an ignition assistance device. Specifically, this device is installed in a compression ignition engine and designed to enhance ignition in aviation-fueled high-altitude aircraft propulsion systems. The research sheds light on the mechanical impulse caused by the high-speed impact of the spray jet, leading to the accumulation of mechanical stress on the rigid body of the ignition assistance device. Previous studies on fluid-structure interaction have only considered the interaction between the gas phase and the solid wall. However, the SIWS model incorporates the additional impact of the impinging liquid spray jet. Consequently, the simulated stress distribution on the ignition assistance device can be estimated by considering both the gas-phase-induced term and the spray-induced term simultaneously.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Multi-Scale Land-Atmosphere Interactions: Modeling Convective Processes from Plants to Planet

Research accomplishments include: 1)Two case studies of the effects of heterogeneous soil moisture and surface energy budgets on organization and propagation of convective precipitation during MC3E. 2) Development and evaluation of a new approach for simulating the effect of heterogeneous soil moisture at ARM-SGP using an innovative modeling approach. 3) Investigation of the effects of spatial coupling scale using multidecade global simulations in CESM with the multiscale modeling framework. 4) Exploration of changes to future precipitation intensity resulting from two different climate change scenarios using the multiscale model. 5) Provision of the new cloud-scale coupled multiscale Earth System Model to the larger community through the CESM process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Nine Canyon Long-Duration Energy Storage: A Feasibility Study

The Nine Canyon Long Duration Energy Storage (LDES) Feasibility Study explores the technical and economic viability of deploying advanced energy storage technologies at Energy Northwest's (EN) Nine Canyon (9C) Wind Project site in Benton County, Washington. Supported by the Washington State Department of Commerce and the U.S. Department of Energy’s Office of Electricity under its LDES Voucher Program, the study represents a collaborative effort between EN, Pacific Northwest National Laboratory (PNNL), and ARES North America. At the core of this effort is the development of a generalized techno-economic modeling framework and evaluation tool designed to assess the value proposition of LDES projects across a variety of contexts. The modeling tool is technology-agnostic and accommodates user-defined parameters such as rated power, energy duration, round-trip efficiency, capital and operational costs, and dispatch constraints. It also integrates economic inputs, including market prices, energy revenue structures, and financing parameters to evaluate performance through key metrics. The tool provides utilities with a transparent, adaptable platform to support decision-making, investment prioritization, and portfolio planning for various storage technologies. To guide scenario design and interpretation, the study first surveyed the LDES technology landscape, including lithium-ion batteries, flow batteries, non-hydro gravity storage, and thermo-mechanical systems, comparing cost trajectories, technical performance, safety and hazards, materials sourcing and recyclability, and spatial/siting considerations. This literature-grounded review highlights technology trade-offs and reinforces the need to align technology choice with site characteristics, use cases, and project objectives. A companion chapter examines ownership structures (EN ownership, third-party ownership, shared models) and offtake options (energy marketing, capacity/energy PPAs, time-of-use PPAs, block-delivery PPAs, and tolling), where PPAs (power purchase agreements) represent contractual arrangements for buying and selling electricity. The chapter also highlights implications for risk allocation, capital access, operational control, and revenue certainty. The study also evaluates supervisory control and data acquisition (SCADA) and transmission interconnection pathways, options include upgrading the existing SCADA or deploying a dedicated LDES controller, with attention to protection schemes, data telemetry, cybersecurity, and regulatory coordination with BPA. In addition, an ARES-specific geotechnical and hydrology assessment presented in the appendix screens multiple corridors for slope stability, bearing capacity, cut-and-fill magnitude, and stormwater behavior.

25 ENERGY STORAGE↗
NASA NTRS2011

Experimental Determination of the Dynamic Hydraulic Transfer Function for the J-2X Oxidizer Turbopump: Methodology - Part One

An advanced methodology for extracting the hydraulic dynamic pump transfer matrix (Yp) for a cavitating liquid rocket engine turbopump inducer+impeller has been developed. The transfer function is required for integrated vehicle pogo stability analysis as well as optimization of local inducer pumping stability. Laboratory pulsed subscale waterflow test of the J-2X oxygen turbo pump is introduced and our new extraction method applied to the data collected. From accurate measures of pump inlet and discharge perturbational mass flows and pressures, and one-dimensional flow models that represents complete waterflow loop physics, we are able to derive Yp and hence extract the characteristic pump parameters: compliance, pump gain, impedance, mass flow gain. Detailed modeling is necessary to accurately translate instrument plane measurements to the pump inlet and discharge and extract Yp. We present the MSFC Dynamic Lump Parameter Fluid Model Framework and describe critical dynamic component details. We report on fit minimization techniques, cost (fitness) function derivation, and resulting model fits to our experimental data are presented. Comparisons are made to alternate techniques for spatially translating measurement stations to actual pump inlet and discharge.

Zoladz, Tom↗
DOE OSTI2026

Generative Thermodynamic Computing

Here, we introduce a generative modeling framework for thermodynamic computing, in which structured data are synthesized from noise by the natural time evolution of a physical system governed by Langevin dynamics. While conventional diffusion models use neural networks to perform denoising, here the information needed to generate structure from noise is encoded by the dynamics of a thermodynamic system. Training proceeds by maximizing the probability with which the computer generates the reverse of a noising trajectory, which ensures that the computer generates data with minimal heat emission. We demonstrate this framework within a digital simulation of a thermodynamic computer. If realized in analog hardware, such a system would function as a generative model that produces structured samples without the need for artificially injected noise or active control of denoising.

Whitelam, Stephen [Lawrence Berkeley National Labo↗
DOE OSTI2021

Flow Assisted Evaporative Cooling for Electric Motor

This paper examines a novel concept of flow assisted latent heat driven two-phase evaporative cooling (EC) confined in-between slot liner and active-winding of electric motor. Wicking micro-structure enhanced PDMS liner axially sucks coolant in the form of thin film between the PDMS liner and active-winding and eventually enables thin film evaporation on the outer surface of the active-winding. Therefore, EC based thermal management eliminates contact resistance between the winding and slot-liner and, enhances the heat extraction from the winding without compromising the electro-magnetic performance. Two-way coupled electro-magnetic (EM) – computational fluid dynamics/heat transfer (CFD/HT) and EM - lumped parameter thermal network (LPTN) models have been developed to assess the electro-thermal performance of the EC under steady and transient conditions. Taking a case study of a 125 kW jacket cooled BMW i3 motor and dielectric coolant FC-84, EC is shown to be capable of handling a maximum steady state rms current density of 26 A/mm2 at a evaporative heat transfer coefficient of 5,000 W/m2.K, which is about 78.7% higher compared to the traditional jacket cooling (JC). In case of EC, a maximum steady state and transient rms current density of 30 A/mm2 (106.2% higher compared to the JC), and 40.8 A/mm2 have been realized by using high thermal conductivity epoxy (1.9 W/m.K) impregnation material. Thermal performance of the EC is also assessed and compared with JC over a dynamic drive cycle. Lastly, a motorette testing has been performed to demonstrate the applicability of the proposed EC method and to validate the developed modeling framework.

42 ENGINEERING↗
NASA NTRSDate not supplied

Magnetic Mapping in the Inner Magnetosphere using Kamodo

Many models require specialized access and interpolation schemes to effectively extract and interpolate their outputs. In particular, the Block-Adaptive Tree Solarwind Roe Upwind Scheme (BATSRUS) component of the Space Weather Modeling Framework (SWMF) requires Kamodo to take advantage of its block-based adaptive grid structure, and the Lyon-Fedder Mobarry magnetosphere model (or its successor GAMERA) needs a scheme that appreciates the distorted spherical arrangement of grid vertices on a non-orthogonal grid. With the flythrough layer developed by Ringuette et al. (SH42E-2337), the underlying model readers have been adapted to use multiple time steps in a single Python session to perform 4- dimensional interpolations in time and space. Kamodo now utilizes lazy interpolation that loads data only when needed. We present the successful integration of SWMF/BATSRUS magnetosphere access and interpolation into the new 4D Kamodo framework utilizing an external library of C code. Through function composition, Kamodo facilitates the calculation of derived quantities and the transformation of positions and vectors into different coordinate systems. This work is a significant step towards performing field line tracing in Kamodo with SWMF magnetosphere outputs.

Lutz Rastaetter↗
DOE OSTI2026

Discrete versus continuous: Enhancing battery optimization in capacity expansion models

This study compares two battery modeling approaches for capacity expansion models: discrete-duration and continuous-duration formulations. In the discrete approach, battery duration is fixed, and power capacity is optimized. In the continuous approach, both power and energy capacities are decision variables, allowing storage duration to be optimized endogenously. Although both discrete-duration and continuous-duration battery formulations are used in long-term power system planning models, the literature has provided limited direct, systematic comparisons of their implications within a common modeling framework. To address this gap, this study implements both approaches in the Regional Energy Deployment System (ReEDS TM ) capacity expansion model using two resource adequacy methods, across a range of future system conditions, and with varying battery cost projections. Results show continuous-duration and high-resolution discrete approaches produce similar capacity expansion outcomes. The continuous formulation achieves faster runtimes compared to discrete-duration runs with many discrete-duration options. However, the discrete-duration approach allows users to choose to have limited fidelity for storage duration options, which in some cases can outperform the continuous formulation. The continuous formulation has the lowest overall system costs, indicating its ability to fine-tune storage duration to better meet specific system needs. This study's findings provide a side-by-side evaluation of discrete and continuous battery modeling approaches and offer guidance for improving the representation of real-world systems, flexibility, and computational efficiency for representing energy storage in long-term power system planning models.

25 ENERGY STORAGE↗
DOE OSTI2022

Wind turbine response in waked inflow: A modelling benchmark against full-scale measurements

Predicting the power and loads of wind turbines in waked inflow conditions still presents a major modelling challenge. It requires the accurate modelling of the atmospheric flow conditions, wakes of upstream turbines and the response of the turbine of interest. Rigorous validations of model frameworks against measurements of utility-scale wind turbines in such scenarios remain limited to date. In this study, six models of different fidelity are compared against measurements from the DanAero experiment. The two benchmark cases feature a full-wake and partial-wake scenario, respectively. The simulations are compared against local pressure forces and inflow velocities measured on several blade sections of the downstream turbine, as well as met mast measurements and standard SCADA data. Regardless of the model fidelity, reasonable agreements are found in terms of the wake characteristics and turbine response. For instance, the azimuth variation of the mean aerodynamic forces acting on the blade was captured with a mean relative error of 15-20%. Additionally, while various model-specific deficiencies could be identified, the study highlights the need for further full-scale measurement campaigns with even more extensive instrumentation. Furthermore, it is concluded that validations should not be limited to integrated and/or time-averaged quantities that conceal characteristic spatial or temporal variations.

17 WIND ENERGY↗
DOE OSTI2024

A Pathway Analysis Framework for Evaluating the Economic and Environmental Viability of Biomass-Based Plastic Production

Plastic production from fossil feedstocks (e.g., naphtha, coal, and natural gas) is not sustainable and causes known environmental impacts such as global warming. A possible solution is to shift production pathways to use biomass, which is a sustainable feedstock that can sequester atmospheric carbon dioxide. This study presents an optimization-based pathway analysis framework for evaluating the carbon footprints of the production of mainstream plastics from biomass and fossil feedstocks. We use the modeling framework to quickly navigate complex interdependencies that exist between the production pathways of different plastics and to determine pathways of minimum production cost under a range of carbon pricing scenarios. The framework interprets carbon prices as an exogenous taxation scheme or an endogenous negative value perceived by producers. The proposed approach reveals the biomass feedstock quantities needed to displace fossil counterparts and the plastics and technologies that should be prioritized. The framework can also be used for evaluating system-wide trade-offs between production costs and carbon footprints that arise from pathway interdependencies. We also evaluate hidden environmental impacts associated with the large-scale use of biomass as a feedstock, such as land use and water eutrophication that results from a significant increase in fertilizer use. Therefore, it is important to highlight that there are trade-offs between decarbonization and other environmental issues. Here, the proposed framework provides an integrative platform for basic techno-economic and life-cycle data that can be used for analyzing diverse scenarios and determining necessary technology targets (e.g., yields, footprints, and costs) to achieve required levels of decarbonization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Co-scheduling Ensembles of In Situ Workflows

Molecular dynamics (MD) simulations are widely used to study large-scale molecular systems. HPC systems are ideal platforms to run these studies, however, reaching the necessary simulation timescale to detect rare processes is challenging, even with modern supercomputers. To overcome the timescale limitation, the simulation of a long MD trajectory is replaced by multiple short-range simulations that are executed simultaneously in an ensemble of simulations. Analyses are usually co-scheduled with these simulations to efficiently process large volumes of data generated by the simulations at runtime, thanks to in situ techniques. Executing a workflow ensemble of simulations and their in situ analyses requires efficient co- scheduling strategies and sophisticated management of computational resources so that they are not slowing down each other. In this paper, we propose an efficient method to co-schedule simulations and in situ analyses such that the makespan of the workflow ensemble is minimized. We present a novel approach to allocate resources for a workflow ensemble under resource constraints by using a theoretical framework modeling the workflow ensemble’s execution. We evaluate the proposed approach using an accurate simulator based on the WRENCH simulation framework on various workflow ensemble configurations. Results demonstrate the significance of co-scheduling simulations and in situ analyses that couple data together to benefit from data locality, in which inefficient scheduling decisions can lead to slowdown in makespan up to a factor of 30.

Do, Tu Mai Anh↗
DOE OSTI2025

Ecovoltaic solar energy development can promote grassland bird communities

Ecologically informed photovoltaic (PV) developments that co-prioritize PV electricity generation with ecosystem function (‘ecovoltaics’) have emerged as a promising land sharing strategy to minimize ecological conflicts associated with PV solar energy development. While habitat-focused ecovoltaic designs can conceptually benefit biodiversity by offsetting or enhancing impacts of PV development, foundational field research is needed to examine how wildlife respond to these novel ecosystems. We conducted passive acoustic monitoring (PAM) in 2023 and 2024 at 13 solar facilities and paired control sites to investigate avian community responses to ecovoltaic facilities in the Midwestern United States. Compared to control sites (row crop agricultural fields), we found that ecovoltaic sites supported more grassland bird species throughout a 17-week monitoring period between May and September. Grassland bird communities on ecovoltaic sites were also more stable than on agricultural controls, as measured by the Jaccard dissimilarity index. We also used PAM-based weekly species occurrences in an occupancy-modelling framework to investigate the influence of PV development and other landscape variables on grassland bird occupancy. 10 out of 13 modelled grassland bird species had greater predicted occupancy probabilities (ψ) on PV sites than control sites. Synthesis and applications. Our findings suggest that properly sited and developed ecovoltaic solar facilities in human altered landscapes can improve habitat for birds and other wildlife, but further research is needed to understand which species may benefit most from these novel ecosystems.

14 SOLAR ENERGY↗
DOE OSTI2026

Data for Zheng et al. (2025), "AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry"

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystems and soil function. Salinity affects soil carbon cycling by directly impacting microbial activity and indirectly altering soil physicochemical properties, but current models inadequately represent these complexities. This dataset contains the observational and modeling data from Zheng et al. (2025), which described a process-based modeling framework that couples soil solution chemistry with microbial carbon cycling reactions to study the impacts of soil salinization. This conceptual model is implemented numerically into the open-source geochemical program PHREEQC 3.0 (Parkhurst and Appelo, 2013). This dataset consists of: - Figure2_AquaMEND_salinity_buffer: Contains model simulation outputs to assess the impact of three different cation exchange and surface complexation processes on salinity buffering (Fig. 2 from Zheng et al. 2025). - Figure3_Salinity_function: Contains salinity function fitting for literature data (Fig. 3 from Zheng et al. 2025). - Figure4_AquaMEND_microbial_mechanisms: Contains model simulation outputs for testing various microbial process-based hypotheses related to soil salinization, including microbial mortality, carbon use efficiency (CUE), extracellular enzyme activity, and other microbial mechanisms (Fig. 4 from Zheng et al. 2025). - Figure5_AquaMEND_Redox: Contains on model simulation outputs to evaluate shifts among key redox processes, such as aerobic respiration, sulfate reduction, and methanogenesis (Fig.5 from Zheng et al. 2025). - Figure6_AquaMEND_sorption: Contains on model simulation outputs for investigating the effects of salinity on dissolved organic matter (DOM) sorption and desorption processes (Fig. 6 from Zheng et al. 2025). - Figure7_AquaMEND_process_couple: Contains on model simulation outputs for exploring coupled biotic-abiotic processes and their interactions (Fig. 7 from Zheng et al. 2025). - data: Includes datasets used to develop salinity response functions and evaluate salinity buffering capacity. Datasets for MEND model calibration. - database: Contains the `.dat` file required by PHREEQC for model execution. - README.md: A Markdown plain text file describing the computational tools and directories. Files are a mixture of plain text CSV (comma-separated value) and plain text *.dat files written by the model; no special software is required to read them.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL SALINIT↗
DOE OSTI2023

The Role of Hydropower Flexibility in Integrating Renewables in a Low-Carbon Grid

In this study, we looked at the role of hydropower flexibility in variable renewable energy (VRE) integration. Our focus was on facilities that have at least ten hours of storage, i.e., plants that are "dispatchable" and have capacity values similar to that of fossil-fired generation. For our modeling framework, we used NREL's Mid-Case/95% Carbon Reduction by 2035 standard scenario as our foundation. This zonal model is representative of the buildout of a near-zero carbon policy grid in an otherwise "business-as-usual" policy and economic environment. We chose this scenario because it aligns well with the Administration's net-zero carbon grid by 2035 goal.

13 HYDRO ENERGY↗
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↗