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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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A summary of updates to the electricity bill calculator in the most recent version of the System Advisor Model including changing the true-up month and new compensation options for metering and billing. Also included a preview of features in the upcoming release, such as billing demand for energy charges.
The bioeconomy represents an advanced economic paradigm that builds upon previous agricultural, industrial, and digital economic models. It seeks to tackle critical global challenges such as resource scarcity, escalating healthcare demands, and environmental degradation. At the heart of the bioeconomy is biomanufacturing, which uses natural or engineered enzymes or cell factories built from biological components like promoters, terminators, regulatory sequences, reporters, and functional genes into various chassis hosts (including animal, microbial, plant, and de novo systems) to create products such as food, energy, medicine, materials, chemicals, and engineered tissue/organs. An enabler of biomanufacturing is biodesign – also known as biosystems design and closely related to synthetic biology or engineering biology. This interdisciplinary field aims to understand and predictably modify existing life forms or create entirely new biological entities/systems using rational engineering strategies and automated design tools. Through these capabilities, biodesign supports the discovery, optimization, and creation of efficient platforms for biomanufacturing.
Nutrient use efficiency (NUE) is typically measured as the ratio of yield to soil nutrient availability but ignores contributions of underlying plant traits. Relevant plant traits can be grouped as root acquisition efficiency, shoot radiation use efficiency, and plant metabolic efficiency. The intentional integration of these traits will lead to synergistic improvements of NUE. Recent progress in trait-focused research includes phenotyping root nutrient uptake rates and respiration, engineering reduced photorespiration, and identification of nutrient assimilation pathways. Traits need to be conceptualized in agricultural systems contexts to improve synchrony of plant demand and soil supply of nutrients, including consideration of crop mixtures. Use of simulation modeling and multi-objective optimization will allow accelerating NUE gains beyond selection for a single ratio.
Abstract Water resources systems models enable valuable inferences on consequential system stressors by representing both the geophysical processes determining the movement of water and the human elements distributing it to its various competing uses. This study contributes a diagnostic evaluation framework that pairs exploratory modeling with global sensitivity analysis to enhance our ability to make inferences on water scarcity vulnerabilities in institutionally complex river basins. Diagnostic evaluation of models representing institutionally complex river basins with many stakeholders poses significant challenges. First, it needs to exploit a large and diverse suite of simulations to capture important human‐natural system interactions as well as institutionally aware behavioral mechanisms. Second, it needs to have performance metrics that are consequential and draw on decision‐relevant model outputs that adequately capture the multisector concerns that emerge from diverse basin stakeholders. We demonstrate the proposed model diagnostic framework by evaluating how potential interactions between changing hydrologic conditions and human demands influence the frequencies and durations of water shortages of varying magnitudes experienced by hundreds of users in a subbasin of the Colorado River. We show that the dominant factors shaping these effects vary both across users and, for an individual user, across percentiles of shortage magnitude. These differences hold even for users sharing diversion locations, demand levels or water right seniority. Our findings underline the importance of detailed institutional representation for such basins, as institutions strongly shape how dominant factors of stakeholder vulnerabilities propagate through the complex network of users.
Abstract Atmospheric dryness (i.e., high vapor pressure deficit, VPD), together with soil moisture stress, limits plant photosynthesis and threatens ecosystem functioning. Regions where rainfall and soil moisture are relatively sufficient, such as the rainfed part of the U.S. Corn Belt, are especially prone to high VPD stress. With globally projected rising VPD under climate change, it is crucial to understand, simulate, and manage its negative impacts on agricultural ecosystems. However, most existing models simulating crop response to VPD are highly empirical and insufficient in capturing plant response to high VPD, and improved modeling approaches are urgently required. In this study, by leveraging recent advances in plant hydraulic theory, we demonstrate that the VPD constraints in the widely used coupled photosynthesis‐stomatal conductance models alone are inadequate to fully capture VPD stress effects. Incorporating plant xylem hydraulic transport significantly improves the simulation of transpiration under high VPD, even when soil moisture is sufficient. Our results indicate that the limited water transport capability from the plant root to the leaf stoma could be a major mechanism of plant response to high VPD stress. We then introduce a Demand‐side Hydraulic Limitation Factor (DHLF) that simplifies the xylem and the leaf segments of the plant hydraulic model to only one parameter yet captures the effect of plant hydraulic transport on transpiration response to high VPD with similar accuracy. We expect the improved understanding and modeling of crop response to high VPD to help contribute to better management and adaptation of agricultural systems in a changing climate.
Architectural thermo-responsive dynamic windows offer an autonomous solution for solar heat regulation, thereby reducing building energy consumption. Previous work has emphasized the significance of thermo-responsive windows in hot climates due to their role in solar heat control and subsequent energy conservation; conversely, our study provides a different perspective. Through a global-scale analysis, we explore over 100 material samples and execute more than 2.8 million simulations across over two thousand global locations. World heatmap results, derived from well-trained artificial neural network models, reveal that thermo-responsive windows are especially useful in climates where buildings demand both heating and cooling energy, whereas thermo-responsive windows with optimal transition temperatures show no dynamic features in most of low-latitude tropical regions. Additionally, this study provides a practical guideline and an open-source mapping tool to optimize the intrinsic properties of thermo-responsive materials and evaluate their energy performance for sustainable buildings at various geographical scales.
The integrated hydrogen energy system incorporates hydrogen energy into the power grid, which has been recognized as a promising option for reaching a 100% renewable electricity supply. It can make a profit because the hydrogen produced can be sold as fuel or used to generate electricity for grid services. In this paper, we develop a planning model for the integrated hydrogen energy system that considers the uncertainty of the load demand, the renewable energy generation, and the market prices. To calculate the hydrogen load, we simulate the refueling operations at a hydrogen fueling station over the course of one day and generate representative load profiles with K-means clustering. Moreover, the long-term profitability of the integrated system under both current and future conditions is validated in 10-year planning results.
Driven by the exceedingly high computational demands of simulating mechanical response in complex engineered systems with finely resolved finite element models, there is a critical need to optimally reduce the fidelity of such simulations. The minimum required fidelity is constrained by error tolerances on the simulation results, but error bounds are often impossible to obtain a priori. One such source of error is the variability of material properties within a body due to spatially non-uniform processing conditions and inherent stochasticity in material microstructure. This study seeks to quantify the effects of microstructural heterogeneity on component- and system-scale performance to aid in the choice of an appropriate material model and spatial resolution for finite element analysis.
As part of the U.S. Agency for International Development (USAID)-National Renewable Energy Laboratory (NREL) Young Leaders Workforce Training Program in Colombia, the Grupo Energía Bogotá (GEB) participants leveraged their training and professional experience to develop an action plan for modeling and evaluating Bogotá's projected electric vehicle (EV) charging needs to meet future demand. This case study summarizes the collaboration between USAID-NREL, GEB, and the Bogotá Department of Transportation Mobility Secretariat (SDM) to estimate EV charging station needs to meet projected future EV sales in the city of Bogotá and determine high-priority locations within the greater Bogotá metropolitan area for planning and applying EVSE investment and installation.
Buildings are a major consumer of electricity in the United States and a significant portion of the consumption comes from heating, ventilation, and air-conditioning (HVAC) applications. Passive cooling strategies in the building envelope help to reduce the energy consumption for HVAC as well as peak electricity demand. Although being one of the most cost-effective passive cooling strategies, modern reflective roofing and reflective exterior wall technology is not well documented for its impact on peak demand. This study utilized whole building energy simulations on residential and commercial building prototype models to quantify the impact of cool roofs and cool exterior walls. The analysis was performed in three climate zones with varying insulation levels and solar reflectances for roofs and exterior walls. For both the residential and commercial buildings, the baseline building had a roof solar reflectance value of 0.10 and an exterior wall solar reflectance value of 0.25. The results from the simulations show that roofs and exterior walls with higher reflectance values increase cooling energy savings but can also increase heating energy consumption. The impact of changes in solar reflectances was greater in buildings with low roof/wall insulation levels compared to roofs/walls with higher insulation levels. A baseline for the simulations was set with the roof and exterior wall solar reflectances set at 0.1 and 0.25, respectively and simulations having varying roof and exterior wall thermal resistances were compared to the baselines.
This report presents an unreliability evaluation of the residual heat removal (RHR) system in two modes of operation (low-pressure injection in response to a large loss-of-coolant accident and in response to post-trip shutdown cooling) at 93 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database. The unreliability results are trended for the most recent 10-year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the RHR results.
This report presents an unreliability evaluation of the high-pressure safety injection system (HPSI) at 62 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hours, and failure data from calendar years 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10-year period while yearly estimates for system unreliability are provided for the entire active period. Highly statistically significant increasing trends were identified in both the HPSI system start-only unreliability and 8-hour mission unreliability.
This report presents an unreliability evaluation of the isolation condenser (ISO) system at three U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from calendar year 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the ISO results.
This report presents an unreliability evaluation of the high-pressure core spray (HPCS) at eight U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10-year period while yearly estimates for system unreliability are provided for the entire active period. Statistically significant increasing trends were identified in both the HPCS system start-only unreliability and 8-hour mission unreliability.
This report presents an unreliability evaluation of the high-pressure coolant injection (HPCI) system at 22 U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPCI results.
This report presents an unreliability evaluation of the emergency power system (EPS) at 93 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the industry-wide estimates of EPS system start-only unreliability, but a highly statistically significant decreasing trend was identified in the industry-wide estimates of EPS system 8-hour mission unreliability.
This report presents an unreliability evaluation of the auxiliary feedwater (AFW) system at 62 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from calendar year 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the industry-wide estimates of AFW system start-only unreliability, but a highly statistically significant decreasing trend was identified in the industry-wide estimates of AFW system 8-hour mission unreliability.
This report presents an unreliability evaluation of the reactor core isolation cooling (RCIC) system at 28 U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from calendar years 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. Statistically significant decreasing trends were identified in both the RCIC system start-only unreliability and 8-hour mission unreliability.