Progress in alternative neutron detection to address the helium-3 shortage
Not Available
Kouzes, Richard T.↗
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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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Sensitivity Analysis of Drivers Water Shortage in the Los Angeles Region During Drought
The code and detailed step-by-step instructions for generating the model output data, processing results, and analysis and plotting are provided at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. The PyArtes model is a python adaptation of the Artes model. PyArtes uses many of the same input data and optimization model architecture as Artes. Documentation for the PyArtes model is provided in the Supplement to the paper. The primary data product are simulated monthly water shortages for indoor and outdoor demand under a large ensemble of drought scenarios (>13,000). The droughts are hypothetical and are not based on historical time series data of supply sources - though historical data did help inform ranges explored for supply parameters. Demands are informed by recent 2017-2021 water supply data. Demands used for the model can be accessed at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. Simulations resolve demand for over 90 water providers in the study region. The results report 36 months of water shortage data for each indoor and outdoor demand node. The study also developed a multilayer perceptron (MLP) neural network trained on a subset of the simulated shortage ensemble to emulate worst annual water shortage for a given set of parameter multipliers -- provided the parameter values fall within the ranges sampled in the ensemble. Emulated water shortages for synthetic ensembles are in the MLP-generated shortages folder. The MLP model was used to generate larger ensembles to support Sobol analysis that would have been extremely computationally expensive to simulate. Datasets provided in this repository*: Simulated shortages. These results are used for the analysis for Figures 5, 8, and 9 in the paper, and also to train the MLP emulator. .zip file containing outputs for the 13,312 scenario ensemble. Separate .csv files for indoor and outdoor shortage for each scenario. Rows = demand ids (~100), Columns = months (36) Units = acre-feet/month of shortage (shortage = monthly demand - supply). 1 acft = 1233.48 m^3 .csv files of aggregated shortages derived from the 13,312 ensemble Rows = scenarios (13,312), Columns = demand ids (~100) Units = acre-feet/year (either worst annual shortage or total shortage over the 3-year drought) .csv file of the parameter multipliers scenarios for the ensemble .csv file of the parameter ranges and baseline values the multipliers were applied to MLP-generated shortages. These results are used for Figures 4, 6, and 7 in the paper. mwd higher folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results Emulated shortages. Rows = scenarios, columns = demand ids, units acft Sobol results. Rows = demand ids, columns Sobol (S1, ST, or 95% confidence interval) value for each parameter mwd lower folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results same organization as mwd higher MLP performance: performance metrics (R^2, RMSE, BIAS, MAPE) for the testing subset (20% or 2,662 scenarios) and simulated vs emulated worst year shortage (acre-feet/year) for every demand node, MWD wholesale regions, and the entire study region (LAC). Supporting data for figures. Figure plotting scripts in the associated GitHub repo. These files support analysis and visualization. Geospatial Data used for plotting simulated water shortages and Sobol results. Dictionary of full names for demand nodes in the model and estimates of water supply by source type informed by Artes input files and California Urban Water Management Planning data: https://water.ca.gov/Programs/Water-Use-And-Efficiency/Urban-Water-Use-Efficiency/Urban-Water-Management-Plans *Readme files provided for each folder.
drought↗
Power generation-cooling water Nexus: Impacts of cooling water shortage on power system operation - a simulation case study in Illinois, U.S
Cooling water shortage, frequently attributed to drought and heat waves, poses a significant threat to the operations of thermoelectric power plants and further poses a challenge for the entire power system and environmental stakeholders. Recognizing the critical nexus between power generation and cooling water availability and the potential ability of power generations to adjust generation schedules during cooling water shortages, this paper introduces a security-constrained unit commitment and economic dispatch model considering water-energy nexus. In specific, the model is augmented with a unit-level cooling water requirement (CWR) model and multi-level cooling water availability (CWA) constraints. The unit-level CWR model quantifies the cooling water withdrawal per MWh of power generation, taking into account factors such as thermoelectric generation technologies, cooling system technologies, and environmental parameters. The multi-level CWA constraints incorporate pump-level, plant-level, watershed-level, and forced minimum power constraints, utilizing data derived from actual-based cooling water shortage scenarios. Using a simulation case study in Illinois, United States, this research examines the reliability, economic, and environmental implications of cooling water shortages on power system operations. The results show that Illinois may experience 10-15% daily load curtailment and severe congestion between certain regions from the east to central during cooling water shortages, while once-through and wet-tower units experience a 52% and 17% reduction in power generation. In conclusion, overall cooling water withdrawal decreases by 24-38% as severity intensifies.
Cooling water shortage↗
Evaluation of U.S. Manufacturing Subsectors at Risk of Physical Water Shortages
The potential impact of water shortages on U.S. manufacturing is unknown. While water for manufacturing constitutes an estimated 6% of U.S. water intake, the data (i.e., location, quantity, and purpose of water intake) needed to determine this impact does not exist. This paper will identify manufacturing subsectors at risk of physical water shortages by applying a method for estimating U.S. manufacturing water intake at the necessary spatial and sectoral resolutions. First, the data requirements to quantify a manufacturing facility’s water footprint within the context of the watershed are developed. Second, using international data, water intake at the national, state, and county-levels by each U.S. manufacturing subsector is estimated. Third, manufacturing subsectors that are most vulnerable to risks of physical water shortages are identified. Based on the results, the Paper, Primary Metals, Chemical, Petroleum and Coal Products, and Food subsectors have the largest intake, respectively. However, the Primary Metals, Fabricated Metals, Transportation Equipment, Petroleum and Coal Products, and Plastics and Rubber subsectors are at the greatest risk of physical water shortages based on concentrations of water intake in water-stressed regions. Lastly, the results can be used to develop strategies to mitigate the risks of water shortages on the U.S. manufacturing sector.
54 ENVIRONMENTAL SCIENCES↗
A Passivity-Shortage Based Control Design for Teleoperation With Time-Varying Delays
This letter investigates the effect of time-varying delays in bilateral teleoperation, with respect to stability and performance, using the properties of passivity-shortage. Until recently, the desired stability and performance characteristics were achieved using the concept of passivity. However, passivity is limited to systems of relative degree zero or one, while passivity-shortage includes systems of higher relative degrees and possibly of non-minimum phase. Passivity-shortage also arises naturally when data transmission is subject to delays, either constant or time-varying. In this letter, the properties of passivity-shortage are employed to design a simple negative feedback controller. We show that the proposed method provides a faster responding solution and improved performance compared to the existing approaches. The performance improvements include improved steady-state error convergence, and robustness against environmental disturbances, even in the presence of varying delays.
42 ENGINEERING↗
Develop a weather-aware climate model to understand and predict extremes and associated power outages and renewable energy shortages with uncertainty-aware and physics-informed machine learning
Focal Area(s): The focus area is predictive modeling through the use of AI techniques and AI-derived model components with a particular emphasis on extreme weather in Atmospheric Science and power outages and shortages in Energy Science. Science Challenge: Predicting weather extremes (e.g., heavy precipitation, strong wind, and large hailstones), and weather-related power system outages and shortages can mitigate economic losses, save lives, support renewables integration, and improve power system resiliency. However, currently, the poor reliability and large uncertainty associated with the weather extreme prediction in the current climate models make the problem intractable. The key challenges are: (1) physical factors like green-house gases (GHGs), aerosols, and land use and land cover (LULC) can significantly impact extreme storms, but the understanding of these impacts is limited, particularly globally; (2) the convective permitting resolutions needed to model severe convective storms and their impacts are computationally prohibitive with global climate models (GCMs); (3) interactions between weather extremes and power system outages are complex and subject to great uncertainty. Current outage prediction models are short lead (~ 3 days), which do not allow for long-time planning of energy production and distribution. Moreover, we have limited capacity to predict weather events leading to sustained shortages in a renewable-energy-dominated power system. These challenges drive motivation for mechanistic understanding and reliable and efficient predictive modeling of extremes and their impacts from the sub-seasonal to long term projections.
54 ENVIRONMENTAL SCIENCES↗
Natural gas shortages during the “coal-to-gas” transition in China have caused a large redistribution of air pollution in winter 2017
The Chinese “coal-to-gas” and “coal-to-electricity” strategies aim at reducing dispersed coal consumption and related air pollution by promoting the use of clean and low-carbon fuels in northern China. Here, we show that on top of meteorological influences, the effective emission mitigation measures achieved an average decrease of fine particulate matter (PM 2.5 ) concentrations of ~14% in Beijing and surrounding areas (the “2+26” pilot cities) in winter 2017 compared to the same period of 2016, where the dispersed coal control measures contributed ~60% of the total PM 2.5 reductions. However, the localized air quality improvement was accompanied by a contemporaneous~15% upsurge of PM 2.5 concentrations over large areas in southern China. We find that the pollution transfer that resulted from a shift in emissions was of a high likelihood caused by a natural gas shortage in the south due to the coal-to-gas transition in the north. The overall shortage of natural gas greatly jeopardized the air quality benefits of the coal-to-gas strategy in winter 2017 and reflects structural challenges and potential threats in China’s clean-energy transition.
54 ENVIRONMENTAL SCIENCES↗
Advancing Diagnostic Model Evaluation to Better Understand Water Shortage Mechanisms in Institutionally Complex River Basins
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.
Hadjimichael, Antonia↗
Environmental and ecological signals predict food shortages for subtropical populations of Australian flying foxes, reservoirs of Hendra virus
Food availability determines where and how animals use space across a landscape and, therefore, affects the risk of encounters leading to zoonotic spillover. This relationship is evident in Australian flying foxes (Pteropus spp.; fruit bats), where acute food shortages precede clusters of Hendra virus spillovers. Using machine learning, we predicted months of food shortages from climatological and ecological covariates (1996–2022) in subtropical Australia. Overall accuracy in predicting months of low food availability on a test set from 2018 up to 2022 reached 93.33 and 92.59% based on climatological and bat-level features, respectively. Seasonality and the Oceanic El Niño Index were the most important environmental features, while the number of bats in rescue centres and their body weights were the most important bat-level features. These models support predictive signals up to nine months in advance, facilitating action to mitigate spillover risk.
Pteropus↗
Acute Shortage Ventilator
Abstract We have implemented an “Acute Shortage Ventilator” (ASV) motivated by the COVID-19 pandemic and the possibility of severe ventilator shortages in the near future. The unit cost per ventilator is less than $400 US excluding the patient circuit parts. The ASV mechanically compresses a self-inflating bag resuscitator, uses a modified patient circuit, and is commanded by a microcontroller and an optional laptop. It operates in both Volume-Controlled Assist-Control mode and a Pressure-Controlled Assist-Control mode. It has been tested using an artificial lung against the EURS guidelines. The key design goals were to develop a simple device with high performance for short-term use, made primarily from common hospital parts and generally-available non-medical components, and at low cost and ease in manufacturing.
Akerib, D. S.↗
Acute shortage ventilator
We have implemented an ″Acute Shortage Ventilator″ (ASV) motivated by the COVID-19 pandemic and the possibility of severe ventilator shortages in the near future. The unit cost per ventilator is less than $400 US excluding the patient circuit parts. The ASV mechanically compresses a self-inflating bag resuscitator, uses a modified patient circuit, and is commanded by a microcontroller and an optional laptop. It operates in both Volume-Controlled Assist-Control mode and a Pressure-Controlled Assist-Control mode. It has been tested using an artificial lung against the EURS guidelines. The key design goals were to develop a simple device with high performance for short-term use, made primarily from common hospital parts and generally-available non-medical components, and at low cost and ease in manufacturing.
Breur, Sander↗
Shortage of Type B LLRW Casks in the US to Serve Nuclear Plants and National Labs - 15663
In early 2012, the industry experienced sudden shortage of Type B Low Level Radioactive Waste (LLRW) transport casks available for transportation of nuclear waste and sealed sources within the United States (US) of America. Some of the events which created this situation include, but not limited to, opening of a new LLRW Disposal facility (Andrews County, TX) managed by Waste Control Specialists (WCS) for Class A, B and C LLRW, retirement of vast majority of previously certified Type B LLRW transport packages, more stringent regulatory certification requirements and increased demand for LLRW transportation casks to support decommissioning of nuclear power plant and transportation of sealed sources. Cask designers are still in the process of responding to the emerging needs of the industry. This paper will provide a detailed background and discuss the events that have occurred in recent years that have led to a shortage of Type B LLRW transport casks available to service the industry with transportation of resins, used filters, irradiated hardware and sealed sources. In addition, this paper will provide an overview of currently available, being fabricated Type B packages as well as information about the tentative designs of Type B LLRW transport casks to be designed and certified in the US by cask design/manufacturing firms in the near future. In conclusion section, this paper will summarize whether the LLRW Type B transport cask supply market for discussed payloads will be able to adequately respond to the industry demand. Potential ways for long term resolution of this issue will be discussed. (author)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Aminophylline shortage and current recommendations for reversal of vasodilator stress: An ASNC information statement endorsed by SCMR
Pharmacologic reversal of serious or intolerable side effects (SISEs) from vasodilator stress is an important safety and comfort measure for patients experiencing such effects. While typically performed using intravenous aminophylline, recurrent shortages of this agent have led to a greater need to limit its use and consider alternative agents. This information statement provides background and recommendations addressing indications for vasodilator reversal, timing of a reversal agent, incidence of observed SISE with vasodilator stress, clinical and logistical considerations for aminophylline-based reversal, and alternative non-aminophylline based reversal protocols.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
An offshore solution to cobalt shortages via adsorption-based harvesting from seawater
The forecasted dominance of electric vehicles and the need for grid-scale energy storage have heightened concerns that cobalt, a key constituent of lithium-ion batteries, could become a critical limiting factor. With limited terrestrial resources and over half the global production coming from politically challenging regions increasing risk, a shortage of cobalt could be experienced by the early 2020s. Fortunately, the oceans contain about 70 times more cobalt than on land and can be harvested sustainably with passive adsorption technologies; and a symbiotic system using existing offshore structures to harvest cobalt could enhance the economic feasibility of seawater cobalt harvesting. Our study finds that retrofitting just 76 unused oil platforms in the Gulf of Mexico could extract an average of 27.3% of the nation’s 2017 cobalt consumption. New Offshore Opportunity for Underwater Cobalt Harvesting has the potential to reduce the cobalt supply pinch point in lithium-ion battery production.
42 ENGINEERING↗
Feb. 2021 Electricity Blackouts and Natural Gas Shortages in Texas
An extreme winter storm and extended cold weather event hit Texas and the central United States February 8–19, 2021. This led to both exceptional energy demands and issues with electricity and natural gas supplies over several days. Residential space heating drove the increases in demand, with over 60% of Texas homes using electric heat pumps and 35% using natural gas furnaces. Supply issues were caused by freezing equipment and supply lines, impacting both natural gas supplies and most forms of electricity generation. [1] Natural gas supplies were especially important because natural gas also supplied about 50% of the electricity generating capacity in ERCOT, the primary grid operator in Texas. [2] Due to the supply shortages, wholesale electricity prices were forced to the ERCOT maximum of $\$9,000$ /MWh for over three days (recent range $\$20$–40/MWh), [3] and natural gas prices for physical delivery exceeded $\$400$ /MMBtu in some areas (recent range $\$3$–4/MMBtu). [4]
03 NATURAL GAS↗
Data for Unraveling the Drivers of Water Shortage across Spatial Scales and Sectors in Colorado's West Slope River Basins
Results from Sunkara et al. submitted to Earth's Future. All code to reproduce the experiment and make the figures can be found here: https://github.com/ssaiveena/Sunkara-etal_2025_WestSlope For a detailed guide to data in this repository, see the README.txt file. Shortage output from .xdd files generated by StateMod was compressed into .parquet files in the Uncertain_scenarios folder. Reservoir output from .xre files can be found in the "Reservoir" directory within the Uncertain_scenarios folder. We adopted the CDSS naming convention: cm = Upper Colorado River Basin gm = Gunnison River Basin ym = Yampa River Basin wm = White River Basin sj = Southwest Basin
Climate Change↗
A Simple Way to Overcome the Shortage of {sup 3}He Detectors in the IPEN/MB-01 Nuclear Reactor
The presented work shows the preliminary results of an experimental procedure to overcome the helium-3 detectors shortage in the IPEN/MB-01 nuclear reactor and be feasible the study of the high subcritical states with less sensitivity detectors. The main principle was employing the input logic nuclear module which was possible to execute logic operations with the neutron signals. Though these signals was possible to construct the Auto Power Spectral Densities (APSD) and obtain the Prompt Neutron Constant Decay (α). Two different kinds of thermal neutron detectors were used ({sup 3}He and BF{sub 3}). The arrangement was initially constituted by one of each type detector and, posteriorly, for a more complete data acquisition, in groups of two detectors for all subcritical configurations. The experiment was carried out using the control banks (BC-1 and BC-2) insertion to achieve all the subcritical states studied in this work. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Sensitivity of future U.S. Water shortages to socioeconomic and climate drivers: a case study in Georgia using an integrated human-earth system modeling framework
Not Available
29 ENERGY PLANNING, POLICY, AND ECONOMY↗