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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Maximizing energy efficiency in wastewater treatment plants: A data-driven approach for waste heat recovery and an economic analysis using Organic Rankine Cycle and thermal energy storage

Maximizing energy efficiency through waste heat recovery (WHR) processes is crucial for sustainable and ecofriendly operations across multiple industries, notably in wastewater treatment plants (WWTPs). This work proposes a comprehensive approach for assessing the WHR feasibility in WWTPs, structured in two main objectives. Firstly, an Artificial Neural Network (ANN) model is developed to accurately predict WHR based on operational data, including biogas temperature, biogas pressure, daily production in kWh, and WHR values in kWh th . The second objective focuses on economically evaluating the WHR feasibility based on the estimated WHR values obtained by the ANN model, and then realistically assessing the economic feasibility of integrating the Organic Rankine Cycle (ORC) and Seasonal Thermal Energy Storage (STES) systems. With an application to the As-Samra WWTP located in Jordan, the developed ANN model demonstrates promising results in the validation phase, with a root mean square error (RMSE) of 2206 kWh/day, a mean absolute error (MAE) of 1674 kWh/day, and an R-squared (R 2 ) value of 68%. On the other hand, the economic analysis reveals that an optimal ORC system of 412.14 kW e capacity yields a Net Present Value (NPV) of 2.09 million US dollars, a Levelized Cost of Energy (LCOE) of 0.0749 USD/kWh, a Payback Period (PBP) of 4.8 years, and annual revenues of 428 kUSD. This work also investigates the techno-economic feasibility of integrating ORC-STES. Results indicate that the LCOE and PBP are highly affected by the ORC's capital cost, and integrating STES increases the LCOE to 0.0824 USD/kWh, rendering its integration with ORC infeasible. In conclusion, this study aims to advance the understanding and application of WHR in WWTPs, paving the way for more efficient and sustainable practices in the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Optimizing Heat Recovery with Storage: Control Validation and Sensitivity Analysis of the Time-Independent Energy Recovery Plant Using Modelica

Heat recovery in large building central plants saves energy but traditionally requires simultaneous heating and cooling. The Time-Independent Energy Recovery (TIER) plant shifts this paradigm by integrating thermal energy storage (TES) to enable heat recovery regardless of concurrent demand, offering a highly efficient, space-saving solution to achieve California’s energy goals. However, its integration of heat recovery chillers, cooling-only chillers, cooling towers, and trim air-source heat pumps (ASHPs) creates growing control and sizing complexity. To overcome this, this study employs high-fidelity Modelica dynamic simulation to validate TIER control sequences and optimize equipment sizing. We translated the written Sequences of Operation into executable Control Description Language (CDL) to test logic against sub-hourly loads. This verification workflow successfully identified and resolved critical vulnerabilities, such as thermal storage freezing and equipment short-cycling, in a virtual environment prior to physical deployment. Then, the study analyzes TIER plant performance across three simulated building types in three locations, and a real building load profile, ensuring variety in heating and cooling loads, and simultaneity factors and explores sizing rules for the TES and ASHP capacity. The analysis shows that the TIER plant operates equipment efficiently leading to a plant SCOP of around 7.5 across all scenarios, higher than a traditional ASHP plant, and a viable pathway to de-risk complex system design and control through simulation to identify optimal designs that maximize energy efficiency, minimize operational costs, and ensure robust operation in varied environmental conditions, thereby facilitating the broader adoption of such a solution for large buildings.

Zanetti, Ettore↗
DOE OSTI2020

Numerical Validation of an Algorithm for Combined Soiling and Degradation Analysis of Photovoltaic Systems

We describe and demonstrate an open-source algorithm for simultaneously quantifying degradation and soiling of photovoltaic (PV) systems from energy-production time series data. The new analysis is based on year-on-year degradation rate analysis combined with stochastic rate and recovery soiling analysis. The algorithm is designed to fit into the workflow provided by RdTools, a Python module maintained by NREL and collaboratively developed with the community, which provides a framework and functions for degradation and loss-factor analysis of PV field data. We demonstrate the method on numerically simulated PV data sets and show that it reduces the root-mean-square error of the P50 degradation rate estimate when soiling is present.

14 SOLAR ENERGY↗
DOE OSTI2022

Economic analysis of precious metal recovery from electronic waste through gas-assisted microflow extraction

The recycling of end-of-life (EoL) electronic products is motivated by the enormous investment of resources in their creation and the environmental concerns associated with electronic waste (e-waste). Hydrometallurgical methods that utilize conventional leaching and solvent extraction are often applied to extract target materials from e-waste; however, these techniques have significant technical and economic limitations when extracting high-value, low concentration metals from complex waste streams. This study proposes and evaluates a novel process based on gas-assisted microflow extraction (GAME) that efficiently recovers precious metals from waste printed circuit boards (WPCBs). Further, an economic analysis is conducted to verify the economic feasibility of the GAME-based process at an industrial scale. The economic outputs are further investigated to identify the most cost-effective production strategies, particularly with respect to the plant feedstock rate. It is envisioned that this study may establish a paradigm for making economically-informed decisions for sustainable technologies.

42 ENGINEERING↗
DOE OSTI2025

Baseline Cost Analysis of Energy Wastewater Treatment with Preliminary Feasibility Analysis of Critical Mineral Recovery

Critical mineral recovery from wastewater is an enhancement of conventional mining that can help meet growing demand. This work investigates two energy wastewaters that have previously been shown to be enriched in critical minerals, oil and gas produced water in the Permian Basin and combustion residual leachate. Treatment of these two wastewaters using reverse osmosis or thermal-based methods concentrates critical minerals, which improves the economic viability of critical mineral recovery. Revenue from mineral recovery could also offset treatment costs for operators. This work evaluates the cost of treatment for each wastewater and evaluates the potential revenue from critical minerals concentrated in the brine. The levelized cost of water for combustion residual leachate ranges from USD 1.90 to USD 16.20 (USD 2023/m 3 permeate) and for produced water ranges from USD 14.40 to USD 24.30 (USD 2023/m 3 distillate). Recovery opportunities range from USD 0.11 to USD 1.13 (USD 2023/m 3 permeate) for leachate and from USD 8.28 to USD 42.10 (USD 2023/m 3 distillate) for produced water, dominated by the value of magnesium and lithium. Comparing the maximum value of critical minerals contained in produced water and the maximum treatment costs, the value of critical minerals exceeds the cost of treatment by USD 17.80/m 3 distillate, which signals a potential revenue opportunity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Multiscale analysis in solids with unseparated scales: fine-scale recovery, error estimation, and coarse-scale adaptivity

There are several engineering applications in which the assumptions of homogenization and scale separation may be violated, in particular, for metallic structures constructed through additive manufacturing. Instead of resorting to direct numerical simulation of the macroscale system with an embedded fine scale, an alternative approach is to use an approximate macroscale constitutive model, but then estimate the model-form error using a posteriori error estimation techniques and subsequently adapt the macroscale model to reduce the error for a given boundary value problem and quantity of interest. Here, we investigate this approach to multiscale analysis in solids with unseparated scales using the example of an additively manufactured metallic structure consisting of a polycrystalline microstructure that is neither periodic nor statistically homogeneous. As a first step to the general nonlinear case, we focus here on linear elasticity in which each grain within the polycrystal is linear elastic but anisotropic.

42 ENGINEERING↗
DOE OSTI2020

Analysis of the thermal recovery of HTS cables after an overcurrent fault

High temperature superconducting (HTS) power transmission cables are cooled to operating temperatures typically below 80 K. A valuable feature of some HTS cables is that they can limit short-circuit fault currents, which can be more than ten times the maximum operating current of a cable. When a fault occurs the HTS wire is no longer superconducting and the heating which occurs will raise the temperature above the allowable operating point. To recover from the fault, the conductor must be cooled down before returning to service. The recovery is affected by the refrigeration system's performance which varies with load and temperature. A transient numerical model of an HTS cable is applied to investigate the thermal recovery after a fault for some HTS cable system configurations and operating conditions.

Demko, Jonathan A.↗
DOE OSTI2024

Critical mineral source potential from oil & gas produced waters in the United States

The volume of produced water, a by-product of oil & gas operations and other energy processes, has been growing across the United States (U.S.) along with the need to manage or recycle this wastewater. Produced water contains many naturally occurring elements of varying concentrations, including critical minerals which are essential to the clean energy transition. However, the current understanding of critical mineral concentrations in produced water and the associated volumes across the U.S. is limited. This study has assessed available databases and literature to gain insight into the presence and concentration of five high priority critical minerals, namely cobalt, lithium, magnesium, manganese, and nickel. The U.S. Geological Survey's National Produced Waters Geochemical Database was the main data source used for determining average critical mineral concentrations in produced water from the major oil and gas reservoirs in the U.S. The volumes of produced water for these major reservoirs were coupled with these concentrations to provide insights into where critical minerals are likely to have high abundance and therefore more recovery options. The analysis indicated the highest recovery potential for lithium and magnesium from produced water in the Permian basin and the Marcellus shale region. However, these assessments should be considered conservative due to the limited availability of reliable concentration data. Finally, it is expected more critical mineral recovery options could emerge with comprehensive characterization data from more recent and representative sources of produced water.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Near-Efficient and Non-Asymptotic Multiway Inference

We establish non-asymptotic efficiency guarantees for tensor decomposition–based inference in count data models. Under a Poisson framework, we consider two related goals: (i) parametric inference , the estimation of the full distributional parameter tensor, and (ii) multiway analysis , the recovery of its canonical polyadic (CP) decomposition factors. Our main result shows that in the rank-one setting, a rank-constrained maximum-likelihood estimator achieves multiway analysis with variance matching the Cramér–Rao Lower Bound (CRLB) up to absolute constants and logarithmic factors. This provides a general framework for studying “near-efficient” multiway estimators in finite-sample settings. For higher ranks, we illustrate that our multiway estimator may not attain the CRLB; nevertheless, CP-based parametric inference remains nearly minimax optimal, with error bounds that improve on prior work by offering more favorable dependence on the CP rank. Numerical experiments corroborate near-efficiency in the rank-one case and highlight the efficiency gap in higher-rank scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Phloem Exudate Protein Profiles during Drought and Recovery Reveal Abiotic Stress Responses in Tomato Vasculature

Drought is the leading cause of agricultural yield loss among all abiotic stresses, and the link between water deficit and phloem protein contents is relatively unexplored. Here we collected phloem exudates from Solanum lycopersicum leaves during periods of drought stress and recovery. Our analysis identified 2558 proteins, the most abundant of which were previously localized to the phloem. Independent of drought, enrichment analysis of the total phloem exudate protein profiles from all samples suggests that the protein content of phloem sap is complex, and includes proteins that function in chaperone systems, branched-chain amino acid synthesis, trehalose metabolism, and RNA silencing. We observed 169 proteins whose abundance changed significantly within the phloem sap, either during drought or recovery. Proteins that became significantly more abundant during drought include members of lipid metabolism, chaperone-mediated protein folding, carboxylic acid metabolism, abscisic acid signaling, cytokinin biosynthesis, and amino acid metabolism. Conversely, proteins involved in lipid signaling, sphingolipid metabolism, cell wall organization, carbohydrate metabolism, and a mitogen-activated protein kinase are decreased during drought. Our experiment has achieved an in-depth profiling of phloem sap protein contents during drought stress and recovery that supports previous findings and provides new evidence that multiple biological processes are involved in drought adaptation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Quantitative analyses of products and rates in polyethylene depolymerization and upcycling

Depolymerization and upcycling are promising approaches to managing plastic waste. However, quantitative measurements of reaction rates and analyses of complex product mixtures arising from depolymerization of polyolefins constitute significant challenges in this emerging field. Here, we detail techniques for recovery and analysis of products arising from batch depolymerization of polyethylene. We also describe quantitative analyses of reaction rates and products selectivity. This protocol can be extended to depolymerization of other plastics and characterization of other product mixtures including long-chain olefins. For complete details on the use and execution of this protocol, please refer to Sun et al.

Lee, Yu-Hsuan↗
DOE OSTI2026

Protein Adhesion on Semi-Fluorinated Polystyrene Surfaces in Static and Dynamic Measurements

Reducing protein adhesion is a critical strategy in fouling-resistant material innovation, with broad applications spanning biomedical and healthcare devices, biosensors, industrial and environmental systems, and other important technological domains. Here, in this study, we elucidated protein adhesion behavior on polystyrene-based thin films by neutron reflectometry (NR) and quartz crystal microbalance with dissipation (QCM-D), using both lysozyme and bovine serum albumin (BSA) as model proteins. To this end, semifluorinated polystyrene thin films with gradient wettability and surface energy were fabricated through dry processing using plasma oxidation and gas-phase deposition. Although it is believed that a fully fluorinated alkyl chain offers extremely low surface energy, thus rejecting foulants, and has been used in many fouling-resistant surface designs, enhanced protein–surface interactions were observed consistently in NR and QCM-D results, due to the combined effects of surface morphology and chemistry. On the contrary, depositing shorter fluorinated silane onto a hydrophilic PS surface contributed to a more homogeneous nanoscale fluorine coating, resulting in less initial protein adsorption and improved surface recovery. Comparative analysis of proteins with different sizes on the nanopatterned semifluorinated surface revealed the influence of molecular characteristics on surface interactions. Lysozyme, being smaller and more compact, showed faster adsorption kinetics and higher surface coverage but largely reversible binding, whereas BSA, with its larger and more flexible structure, formed broader and more stable interfacial layers. This study fills the gap in understanding protein adhesion within the range of hydrophobicity (water contact angle ∼90°), as current strategies often associate with extreme hydrophilic and superhydrophobic surfaces due to hydration or low-surface-energy rejection mechanisms, respectively. It also provides in-depth insights into current combinatorial fouling-resistant surface design.

Yuan, Yue [Oak Ridge National Laboratory (ORNL), O↗
DOE OSTI2024

Simulator Data Analysis to Inform Digitalized Environment Impacts on Human Reliability

The U.S. Nuclear Regulatory Commission (NRC) has developed a human reliability analysis (HRA) method, termed the Integrated Human Event Analysis System for Event and Condition Assessment (IDHEAS-ECA), in order to estimate human error probabilities (HEPs) in risk-informed regulatory applications. To update the quantification part of IDHEAS-ECA, the NRC required human performance and error data from fully digitalized main control rooms (MCRs); therefore, it requested that Idaho National Laboratory (INL) revisit previous data collection studies and investigate how the following three factors impact human reliability: self-checking, peer-checking, and automation. The HRA data collection studies revisited were the Human Reliability Data Extraction (HuREX) project, developed by the Korea Atomic Energy Research Institute (KAERI), and the Simplified Human Error Experimental Program (SHEEP), developed by INL. HuREX is a representative HRA data collection study that collects human reliability data from full-scope simulators staffed by licensed operators. SHEEP, on the other hand, has been proposed to complement such full-scope studies by collecting data via simplified simulators staffed by non-licensed student operators. In the HuREX study, KAERI collected HRA data from fully digitalized MCRs for the Advanced Power Reactor (APR)–1400. The SHEEP data were obtained from simplified simulators that partially mimicked the features of digitalized MCRs. The present report mainly discusses how the impacts of the aforementioned three factors on human errors were derived from these two data collection studies.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Solid Wastes from Geothermal Energy Production and Implications for Direct Lithium Extraction

Direct lithium extraction (DLE) of brines after geothermal power production offers opportunities to produce environmentally benign “green” lithium; however, some environmental impact is inevitable. We examined solid waste production at geothermal power plants in southern California that are also locations for planned DLE facilities. Currently, the geothermal plants in this region produce approximately 79,800 metric tons (wet weight) per year of solid waste, which represents about 28 metric tons per GWh of net electricity production or approximately 500 mg solids per kg geothermal brine. Approximately 15% of this waste requires management as hazardous waste. Solids produced during power production represent about 0.2% of the total dissolved solids in the brine. Lithium production will require the removal of silica, iron, and other metals as part of the DLE process. Using a mass balance approach, we calculate that precipitation of silica and metals could produce up to an additional 6800 mg solids per kg brine. Calcium occurs at very high concentrations, and the amount of solids disposed in landfills will be dependent on the amount of calcium removed during lithium recovery. Our analysis shows that evaluation of brine chemistry in the context of the DLE process is useful for evaluating the potential solid waste impacts of producing lithium from brines.

42 ENGINEERING↗
DOE OSTI2023

Monte Carlo-based Transmission and Subtransmission Recovery Simulation of Hurricanes

High-impact low-probability (HILP) events can wreak havoc on electric power systems without appropriate preparedness. In this paper, the recent development of a tool, named Recovery Simulator and Analysis (RSA), is described and demonstrated. While there are many issues to consider when recovering electric power systems, the focus of RSA is on the coordination of transmission and subtransmission recovery with generation dispatch to minimize unserved energy. RSA focuses on recovery simulation to evaluate resilience as part of a planning process. RSA is demonstrated on an approximately 1400-bus Puerto Rican power system for 100 simulated instances of Hurricane Maria. Analysis of the recovery determines how many lines are critical to the recovery and which loads may experience delayed recovery. The results demonstrate the potential uses of RSA for identifying recovery decisions with low unserved energy and for identifying assets critical to recovery which can then be hardened prior to a HILP event.

Maloney, Patrick R.↗
DOE OSTI2021

Oregon Rivers Characterization Tool

DHS’s Regional Resiliency Assessment Program (RRAP) undertook the Oregon State Transportation Systems RRAP project between 2018-2021 to assess the seismic vulnerabilities of the state’s transportation system to a Cascadia Subduction Zone (CSZ) earthquake (CISA 2021). The project primarily focused on the effects of a CSZ earthquake on the mobility of emergency response efforts into the region. In the event that bridges located at crucial river crossings fail during a CSZ earthquake, rivers will become natural barriers affecting the ability to support response and recovery efforts. The characteristics of rivers (e.g., width, depth, and flow) are critical data to inform planning for the recovery of transportation systems across river barriers and determine reopening times following a CSZ earthquake. As part of the transportation system assessment, an Argonne National Laboratory (Argonne) project team developed a River Characterization Tool (RCT) to quantify the physical characteristics of the river system in Oregon, which can be used to inform a system-level analysis of transportation recovery and reopening times. This report mainly discusses approaches, methods, development, and applications of the RCT. The use of the river data generated from this tool for a system-level analysis of transportation recovery is discussed in the Oregon Transportation Systems RRAP Resiliency Assessment report (CISA 2021). The primary goal of the RCT is to generate statewide dataset of widths, depths, and flows for all rivers across Oregon to assess the effects of river barriers on emergency response and recovery efforts following a CSZ earthquake. The RCT leverages remote sensing data that multispectral sensors collect from satellites, employs a deep learning model to characterize river predictions, and computes river channel geometric dimensions with hydraulic relationships and river predictions. The entire process of river characterization is automated and implemented through the RCT.

58 GEOSCIENCES↗
DOE OSTI2026

Techno-Economic, Feasibility, and Life Cycle Analysis of Renewable Propane: 2025 Update

To clarify the current and future landscape for renewable propane (RP) production, this work evaluates the value proposition of recovering RP from existing and planned hydroprocessed esters and fatty acids (HEFA) biorefineries and surveys emerging technologies under development or deployment. HEFA biorefineries co-produce a propane-rich fuel gas stream, normally used to meet HEFA process heat requirements, from which propane can be recovered and sold to create an additional revenue stream alongside liquid transportation fuels such as renewable diesel (RD) and sustainable aviation fuel (SAF). This report updates and extends a 2022 analysis of RP recovery from HEFA facilities by escalating capital and operating costs to 2024 prices, incorporating recent policy developments (including the Section 45Z Clean Fuel Production Credit), evaluating RP recovery for both RD- and SAF-focused HEFA facilities at two scales (3,000 and 75,000 barrels per day of feedstock), and quantifying the impact of RP recovery on HEFA liquid-fuel carbon intensity (CI) and associated tax credits using the 45ZCF-GREET model. For a 3,000 BPD RD-focused HEFA facility, approximately 3.5 million gallons per year (MGPY) of RP can be recovered; in this base case, the estimated payback period is 18 months based on the total installed cost of the RP recovery equipment and 36 months based on the total capital investment for the entire RP recovery project. The payback period is slightly shorter for the analogous SAF-focused configuration (approximately 4.3 MGPY RP). Sensitivity analysis shows that CAPEX magnitude, RP recovery plant scale, and CI-driven tax credit valuations are the dominant determinants of project viability. RP recovery may increase the CI of HEFA liquid fuels, which can reduce liquid-fuel tax credits (a key revenue stream for the HEFA biorefinery) and lengthen payback periods. However, RP recovery generally remains economically favorable across a wide range of plausible scenarios and market conditions. The report also summarizes emerging pathways that could expand future RP supply.

09 BIOMASS FUELS↗