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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

OptiBench: An Optimization Benchmark Tool for Renewable Energy Problems

We propose a benchmark framework and visualization tool, OptiBench, for analyzing the performance of state-of-the-art optimization solvers across a variety of optimization problems in renewable energy research. Our framework is designed from the ground up in the Julia programming language and enables analysis at scale on high performance computing (HPC) systems. Our visualization tool allows effortless evaluation of optimization solver performance, robustness, and accuracy through intuitive plots, e.g., performance profiles, heat maps, and distribution plots. We have tested three benchmark suites relevant to the modeling of renewable energy systems, viz., CUTEst, PGLib-OPF, and WaterTAP water treatment optimization problems. We illustrate benchmarking of CUTEst using OptiBench on the National Laboratory of the Rockies's (NLR) HPC Kestrel. Our findings indicate that MA57 HSL linear solver demonstrated the best overall performance for an experimental IPOPT implementation. Our work is ongoing and we intend to add support for more optimization solvers and benchmark test suites in the future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Final Technical Report: Transport of Complex Mixtures in Ion-Containing Polymer Membranes

Permselective ion-containing membranes are an integral component for many applications from water treatment, fuel cells, and solar fuels devices where the selective transport of molecules and ions is desired. In solar fuels devices, ion-containing polymer membranes are responsible for permitting selective transport of ions between electrodes to maintain overall charge neutrality yet limit transport of reaction products produced at the electrodes. While the transport of single solutes through such membranes has been fairly well described, binary and multicomponent transport is poorly understood due to the myriad of interactions that occur in these systems (i.e. between co-permeants and between permeants and the membrane). Solar fuels devices are just one example of an application where understanding the transport of multiple simultaneous species is critically important to improving device performance as product crossover leads to reductions in overall device performance. The objectives of this research was to improve our understanding of the complex array of factors that influence transport behavior of multiple solutes within ion-containing polymer membranes. This experimental project addressed the lack of fundamental understanding of multicomponent transport behavior by synthesizing ion exchange membranes with varied incorporation of comonomers (ionic and neutral moieties) to investigate fundamental relationships between membrane structure, membrane physiochemical properties, and transport behavior of solutes and complex solute mixtures through dense, hydrated membranes.

25 ENERGY STORAGE↗
DOE OSTI2025

Muckleshoot Indian Tribe-Energy Deployment (MITED) Project

The Muckleshoot Indian Tribe (MIT) collaborated with our Project Partner, GRID Alternatives (GRID), to install 132 kilowatts of direct current (kW-DC) of rooftop solar on three Tribal facilities. The three facilities are the Tribe’s Youth Drop-In Center, Canoe Shed, and Water Treatment Facility. The solar PV systems were originally anticipated to offset approximately 45% of the aggregate annual electricity usage of the three buildings. A major aspect of the MIT-ED project was providing hands-on paid training to five Muckleshoot Building Maintenance workers in solar PV installations, operations, and maintenance. The scope of work aligns with the Tribe’s goals of building local capacity and providing real world work experience and potential career opportunities in solar PV to its citizens. The Building Maintenance Department committed five of its current FTE employees to the project. GRID provided guidance for the MIT project team on identifying paid trainees as well as end goals of skill development through training, including a long-term Operations and Maintenance (O&M) plan tailored to the Tribe’s goals of local capacity building and stewardship of natural resources.

14 SOLAR ENERGY↗
DOE OSTI2024

Chapter 7.1: Microalgae

Microalgae is a unique biomass resource that does not need to compete for land and water with other biomass feedstocks because it can be cultivated on low-quality unencumbered land using noncompetitive water types including saline and wastewater. It is included as a complementary resource alongside other biomass feedstocks reported in this study, albeit at higher biomass production costs reflective of more capital-intensive farming operations than typical for terrestrial biomass. Higher biomass costs can be offset by the potential to produce value-added coproducts unique to compositional constituents of microalgae. Relative to BT16, this chapter reflects the latest analysis from the 2022 Algae Harmonization Update, which uses the latest parameterized and high-performing saline algal strain, second-generation carbon capture of point-source waste CO2 and high-pressure pipeline transport resolved to specific point-source types, saline water sourcing up to 40,000 mg/L total dissolved solids for source and makeup water salinity, blowdown water treatment and recycle, and brine disposal handling. National-scale algal biomass availability potential was calculated at 152 million tons/yr ash-free dry weight (AFDW) (191 million tons/yr dry weight) at an average biomass productivity of 26.2 g/m2 -day AFDW (about 50 tons/acre/yr dry weight).1 The algal biomass was cultivated on 3.9 million acres of multi-criteria screened and potentially available land for CONUS and fixed 268 million tons of waste CO2 based on biomass uptake. The algae biomass can be produced at an average MBSP of $674/ton AFDW ($536/ton dry weight) in 2020 dollars,2 corresponding to a total energy potential of 3.3 quads/yr at an average MBSP of $31.2/MMBtu (higher-heating-value [HHV] basis).

algae↗
DOE OSTI2021

Molecular Mechanisms of Nanomaterial-Bacterial Interactions Revealed by Omics—The Role of Nanomaterial Effect Level

Nanotechnology is employed across a wide range of antibacterial applications in clinical settings, food, pharmaceutical and textile industries, water treatment and consumer goods. Depending on type and concentration, engineered nanomaterials (ENMs) can also benefit bacteria in myriad contexts including within the human body, in biotechnology, environmental bioremediation, wastewater treatment, and agriculture. However, to realize the full potential of nanotechnology across broad applications, it is necessary to understand conditions and mechanisms of detrimental or beneficial effects of ENMs to bacteria. To study ENM effects, bacterial population growth or viability are commonly assessed. However, such endpoints alone may be insufficiently sensitive to fully probe ENM effects on bacterial physiology. To reveal more thoroughly how bacteria respond to ENMs, molecular-level omics methods such as transcriptomics, proteomics, and metabolomics are required. Because omics methods are increasingly utilized, a body of literature exists from which to synthesize state-of-the-art knowledge. Here we review relevant literature regarding ENM impacts on bacterial cellular pathways obtained by transcriptomic, proteomic, and metabolomic analyses across three growth and viability effect levels: inhibitory, sub-inhibitory or stimulatory. As indicated by our analysis, a wider range of pathways are affected in bacteria at sub-inhibitory vs. inhibitory ENM effect levels, underscoring the importance of ENM exposure concentration in elucidating ENM mechanisms of action and interpreting omics results. In addition, challenges and future research directions of applying omics approaches in studying bacterial-ENM interactions are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Advances in Carbon Capture and Use (CCU) Technologies: A Comprehensive Review and CO2 Mitigation Potential Analysis

One of society’s major current challenges is carbon dioxide emissions and their consequences. In this context, new technologies for carbon dioxide (CO2) capture have attracted much attention. One of these is carbon capture and utilization (CCU). This work focuses on the latest trends in a holistic approach to carbon dioxide capture and utilization. Absorption, adsorption, membranes, and chemical looping are considered for CO2 capture. Each CO2 capture technology is described, and its benefits and drawbacks are discussed. For the use of carbon dioxide, various possible applications of CCU are described, starting with the utilization of carbon dioxide in agriculture and proceeding to the conversion of CO2 into fuels (catalytic processes), chemicals (photocatalytic processes), polymers, and building supplies. For decades, carbon dioxide has been used in industrial processes, such as CO2-enhanced oil recovery, the food industry, organic compound production (such as urea), water treatment, and, therefore, the production of flame retardants and coolants. There also are several new CO2-utilization technologies at various stages of development and exploitation, such as electrochemical conversion to fuels, CO2-enhanced oil recovery, and supercritical CO2. At the end of this review, future opportunities are discussed regarding machine learning (ML) and life cycle assessment (LCA).

Peres, Christiano B.↗
DOE OSTI2020

Assessment of Commercial Building Lighting as a Frequency Regulation Resource

This paper evaluates the potential for automated lighting control as a resource for frequency regulation of the electric grid system in the context of current energy policies, economic incentives, and technological trends. The growing prevalence of renewable energy has increased the need for ancillary services to maintain grid frequency and stability. While demand side resources like heating, ventilating, and air-conditioning systems, as well as water treatment plants are already evaluated as regulation service providers, the potential application to electrical lighting systems has largely been ignored. Yet, aggregations of lighting systems that are retrofitted with intelligent controls could conceivably contribute to frequency regulation services with little impact on user comfort. To further explore the feasibility of lighting potential, this paper explores (1) how lighting control systems are limited by visual comfort perception and acceptability, (2) how such limitations impact the performance of the lighting system as an frequency regulation resource, and (3) how the market potential of lighting systems as demand side resources compares in different regional transmission organizations. Finally, the impact of developing technologies on the application of lighting systems for frequency regulation is discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

In situ EXAFS study of Sr adsorption on TiO 2 (110) under high ionic strength wastewater conditions

In order to provide important details concerning the adsorption reactions of Sr, batch reactions and a set of both ex situ and in situ Grazing Incidence X-ray Absorption Fine Structure (GIXAFS) adsorption experiments were completed on powdered TiO 2 and on rutile(110), both reacted with either SrCl 2 or SrCO 3 solutions. TiO 2 sorption capacity for strontium (Sr) ranges from 550 ppm (SrCl 2 solutions, second order kinetics) to 1400 ppm (SrCO 3 solutions, first order kinetics), respectively, and is rapid. Sr adsorption decreased as a function of chloride concentration but significantly increased as carbonate concentrations increased. In the presence of carbonate, the ability of TiO 2 to remove Sr from the solution increases by a factor of ~4 due to rapid epitaxial surface precipitation of an SrCO 3 thin film, which registers itself on the rutile(110) surface as a strontianite-like phase (d-spacing 2.8 Å). Extended X-ray Absorption Fine Structure (EXAFS) results suggest the initial attachment is via tetradental inner-sphere Sr adsorption. Moreover, adsorbates from concentrated SrCl 2 solutions contain carbonate and hydroxyl species, which results in both inner- and outer-sphere adsorbates and explains the reduced Sr adsorption in these systems. These results not only provide new insights into Sr kinetics and adsorption on TiO 2 but also provide valuable information concerning potential improvements in effluent water treatment models and are pertinent in developing treatment methods for rutile-coated structural materials within nuclear power plants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Synthesis and Characterization of Silver-Modified Nanoporous Silica Materials for Enhanced Iodine Removal

In aquatic environments, the presence of iodine species, including radioactive isotopes like 129 I and I 2 , poses significant environmental and health concerns. Iodine can enter water resources from various sources, including nuclear accidents, medical procedures, and natural occurrences. To address this issue, the use of natural occurring nanoporous minerals, such as zeolitic materials, for iodine removal will be explored. This study focuses on the adsorption of iodine by silver-modified zeolites (13X-Ag, 5A-Ag, Chabazite-Ag, and Clinoptilolite-Ag) and evaluates their performance under different conditions. All materials were characterized using scanning electron microscopey (SEM), energy-dispersive X-ray spectroscopy (EDS), powdered X-ray diffraction (P-XRD), Fourier-transform infrared spectrometry (FTIR), and nitrogen adsorption studies. The results indicate that Chabazite-Ag exhibited the highest iodine adsorption capacity, with an impressive 769 mg/g, making it a viable option for iodine removal applications. 13X-Ag and 5A-Ag also demonstrated substantial adsorption capacities of 714 mg/g and 556 mg/g, respectively, though their behavior varied according to different models. In contrast, Clinoptilolite-Ag exhibited strong pH-dependent behavior, rendering it less suitable for neutral to slightly acidic conditions. Furthermore, this study explored the impact of ionic strength on iodine adsorption, revealing that Chabazite-Ag is efficient in low-salinity environments with an iodine adsorption capacity of 51.80 mg/g but less effective in saline conditions. 5A-Ag proved to be a versatile option for various water treatments, maintaining its iodine adsorption capacity across different salinity levels. In contrast, Clinoptilolite-Ag exhibited high sensitivity to ionic competition, virtually losing its iodine adsorption ability at a NaCl concentration of 0.1 M. Kinetic studies indicated that the pseudo-second-order model best describes the adsorption process, suggesting chemisorption mechanisms dominate iodine removal. Chabazite-Ag exhibited the highest initial adsorption rate with a k 2 value of 0.002 mg g -1 h -1 , emphasizing its superior adsorption capabilities. Chabazite and Clinoptilolite, naturally occurring minerals, provide eco-friendly solutions for iodine adsorption. Chabazite superior iodine removal highlights its value in critical applications and its potential for addressing pressing environmental challenges.

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

Identifying Critical Infrastructure in Imagery Data Using Explainable Convolutional Neural Networks

To date, no method utilizing satellite imagery exists for detailing the locations and functions of critical infrastructure across the United States, making response to natural disasters and other events challenging due to complex infrastructural interdependencies. This paper presents a repeatable, transferable, and explainable method for critical infrastructure analysis and implementation of a robust model for critical infrastructure detection in satellite imagery. This model consists of a DenseNet-161 convolutional neural network, pretrained with the ImageNet database. The model was provided additional training with a custom dataset, containing nine infrastructure classes. The resultant analysis achieved an overall accuracy of 90%, with the highest accuracy for airports (97%), hydroelectric dams (96%), solar farms (94%), substations (91%), potable water tanks (93%), and hospitals (93%). Critical infrastructure types with relatively low accuracy are likely influenced by data commonality between similar infrastructure components for petroleum terminals (86%), water treatment plants (78%), and natural gas generation (78%). Local interpretable model-agnostic explanations (LIME) was integrated into the overall modeling pipeline to establish trust for users in critical infrastructure applications. The results demonstrate the effectiveness of a convolutional neural network approach for critical infrastructure identification, with higher than 90% accuracy in identifying six of the critical infrastructure facility types.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Deep anomaly detection for industrial systems: a case study

We explore the use of deep neural networks for anomaly detection of industrial systems where the data are multivariate time series measurements. We formulate the problem as a self-supervised learning where data under normal operation are used to train a deep neural network autoregressive model, i.e., use a window of time series data to predict future data values. The aim of such a model is to learn to represent the system dynamic behavior under normal conditions, while expect higher model vs. measurement discrepancies under faulty conditions. In real world applications, many control settings are discrete in nature. In this paper, vector embedding and joint losses are employed to deal with such situations. Both LSTM and CNN based deep neural network backbones are studied on the Secure Water Treatment (SWaT) testbed datasets. Also, Support Vector Data Description (SVDD) method is adapted to such anomaly detection settings with deep neural networks. Evaluation methods and results are discussed based on the SWaT dataset along with potential pitfalls.

anomaly detection, deep neural network↗
DOE OSTI2024

The influence of burn severity on dissolved organic carbon concentrations across a stream network differs based on seasonal wetness conditions

Large, high-severity wildfires in many regions across the globe have increased concerns about their impacts on carbon cycling in watersheds. Altered sources of carbon and changes in catchment hydrology after wildfire can lead to shifts in dissolved organic carbon (DOC) concentrations in streams, which can have negative impacts on aquatic ecosystem health and downstream drinking-water treatment. Despite its importance, post-fire DOC responses remain relatively unconstrained in the literature, and we lack critical knowledge of how burn severity, landscape elements, and climate interact to affect DOC concentrations. To improve our understanding of the impact of burn severity on DOC concentrations, we measured DOC at 129 sites across a stream network extending upstream, within, and downstream of a large, high-severity wildfire in Oregon, USA. We collected samples across the study sub-basin during four distinct seasonal wetness conditions. We used our high-spatial-resolution data to develop spatial stream network (SSN) models to predict DOC across the stream network and to improve our understanding of the controls on DOC concentrations. Spatially, we found no obvious wildfire signal – instead, we observed a pattern of increasing DOC concentrations from the high-elevation headwaters to the sub-basin outlet, while the mainstem maintained consistently low DOC concentrations. This suggests that effects from large wildfires may be “averaged” out at higher stream orders and larger spatial scales. When we grouped DOC concentrations by burn severity group, we observed a significant decrease in the variability of DOC concentrations in the moderate and high burn severity sub-catchments. However, our SSN models were able to predict decreases in DOC concentrations with increases in burn severity across the stream network. Decreases in DOC concentrations were also highly variable across seasonal wetness conditions, with the greatest (–1.40 to –1.64 mg L –1 ) decrease occurring in the high-severity group during the wetting season. Additionally, our models indicated that in all seasons, baseflow index was more influential in predicting DOC concentrations than burn severity was, indicating that groundwater discharge can obscure the impacts of wildfire in a stream network. Overall, our results suggested that landscape characteristics can regulate the DOC response to wildfire. Moreover, our results also indicated that the seasonal timing of sampling can influence the observed response of DOC concentrations to wildfire.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Application of Machine Learning to Improve Biobased Glucaric Acid Production: Cooperative Research and Development Final Report, CRADA Number CRD-20-17260

The Agile Biofoundry (ABF) is a multi-national lab consortium funded by the DOE Bioenergy Technologies Office that has developed a biofoundry that enables the rapid deployment of bioproducts into the market. Working with four ABF laboratory members (National Laboratory of the Rockies (NLR), Pacific Northwest National Laboratory (PNNL), Lawrence Berkeley National Laboratory (LBNL), and Argonne National Laboratory (ANL)), Kalion will use advanced high throughput techniques, advanced analytics, and machine learning to optimize the production environment for glucaric acid. Low-cost, high-purity glucaric acid enables products in a wide range of fields to improve the chemical properties of products and applications ranging from water treatment, polymers & textiles, coatings, detergents, and pharmaceuticals. With its broad range of applications, glucaric acid has the potential to demonstrate how such bio-based materials offer great benefit to the US economy.

09 BIOMASS FUELS↗
DOE OSTI2022

Benchmark Model for Wastewater Treatment Using an Activated Sludge Process

This is benchmark model for wastewater treatment using an activated sludge process. The activated sludge process is a means of treating both municipal and industrial wastewater. The activated sludge process is a multi-chamber reactor unit that uses highly concentrated microorganisms to degrade organics and remove nutrients from wastewater, producing quality effluent. This model provides pollutant concentrations, mass balance, electricity requirements, and treatment costs. This model will be continuously updated based on the latest data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1973

Water recovery and solid waste processing for aerospace and domestic applications. Volume 1: Final report

A comprehensive study of advanced water recovery and solid waste processing techniques employed in both aerospace and domestic or commercial applications is reported. A systems approach was used to synthesize a prototype system design of an advanced water treatment/waste processing system. Household water use characteristics were studied and modified through the use of low water use devices and a limited amount of water reuse. This modified household system was then used as a baseline system for development of several water treatment waste processing systems employing advanced techniques. A hybrid of these systems was next developed and a preliminary design was generated to define system and hardware functions.

Murray, R. W.↗
NASA NTRS1974

The Energy Systems Optimization Computer Program /ESOP/ developed for Modular Integrated Utility Systems /MIUS/ analysis

A significant energy and cost savings can be obtained by integrating various utility services (space heating and cooling, electrical power generation, solid waste disposal, potable water, and waste water treatment) into a single unit which provides buildings or groups of buildings with these services. This paper presents a description of a computer program, called the Energy Systems Optimization Program (ESOP). This program predicts the loads, energy requirements, equipment sizes, and life-cycle costs of alternative methods of meeting these utility requirements. The program has been used extensively for performing energy analyses of Modular Integrated Utility Systems (MIUS).

Ferden, S. L.↗
NASA NTRS1979

Dedicated nuclear facilities for electrolytic hydrogen production

An advanced technology, fully dedicated nuclear-electrolytic hydrogen production facility is presented. This plant will produce hydrogen and oxygen only and no electrical power will be generated for off-plant use. The conceptual design was based on hydrogen production to fill a pipeline at 1000 psi and a 3000 MW nuclear base, and the base-line facility nuclear-to-shaftpower and shaftpower-to-electricity subsystems, the water treatment subsystem, electricity-to-hydrogen subsystem, hydrogen compression, efficiency, and hydrogen production cost are discussed. The final conceptual design integrates a 3000 MWth high-temperature gas-cooled reactor operating at 980 C helium reactor-out temperature, direct dc electricity generation via acyclic generators, and high-current density, high-pressure electrolyzers based on the solid polymer electrolyte approach. All subsystems are close-coupled and optimally interfaced and pipeline hydrogen is produced at 1000 psi. Hydrogen costs were about half of the conventional nuclear electrolysis process.

Foh, S. E.↗