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Compilation contains design, performance, and hardware specifications in sufficient detail to fabricate or procure materials and install, operate, and maintain complete modular solar heating and hot water system for single family size dwellings.
IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830
Toxic levels of lead leaching from ageing water distribution infrastructure affect over 5000 public drinking water systems in the US. Pipe replacement, the most effective solution to this problem, is prohibitively expensive. Additionally, chemical conditioning of drinking water using orthophosphates, although cost-effective, does not quickly stop lead leaching once it has started. We propose a novel approach to stop lead leaching: to rapidly form an insoluble scale within lead pipes using an external power supply. We report on the feasibility of this approach by first anodizing lead coupons and lead pipes reclaimed from a local water distribution using a phosphate electrolyte and different potentials, pH values, and phosphate concentrations. We subsequently exposed these anodized lead coupons and pipes to synthetic tap water to evaluate their lead leaching rates. We found that polarizing lead coupons in the presence of a 0.05 M phosphate solution decreased lead leaching by up to a 100-fold, relative to leaching from polished bare lead. Similarly, polarizing the reclaimed lead pipes (with a preexisting scale) decreased lead leaching from an average of 36 ppb to 7 ppb. These results were observed when applying potentials that favor Pb(IV) formation, which resulted in the buildup of PbO 2 and Pb 5 (PO 4 ) 3 OH in both lead coupons and pipes. Our findings indicate that this novel technology has the potential to rapidly decrease equilibrium lead levels in tap water below the EPA action limit of 15 ppb, and thus deserves further exploration.
The emergence of the first life on the earth is now established as an early event, closely related to the evolving earth. Lack of knowledge of the primitive terrestrial conditions contemporary with the evolving prebolic organic chemistry limits reconstruction techniques. The primitive earth's aqueous history is essential to unraveling this problem. Based on current knowledge of other planets of the solar system, no close analog to the early earth can be expected. It is still not known if there was a second origin or if only earth has life. This may depend upon the question of the survival of information-bearing chemical systems in a dynamic or chaotic environment and the chemical protection afforded within such a system. Water is the central molecule of controversy: the blessing and the curse of the chemist. New and novel chemical mechanisms and systems abound.
The modeling of flow systems is a task currently being investigated at Kennedy Space Center in parallel with the development of the KATE artificial intelligence system used for monitoring diagnosis and control. Various aspects of the modeling issues are focussed on with particular emphasis on a water system scheduled for demonstration within the KATE environment in September of this year. LISP procedures were written to solve the continuity equations for three internal pressure nodes using Newton's method for simultaneous nonlinear equations.
All medially related activities of the Space Transportation System 2 flight are described, ranging from preflight to postflight. Several medical problems occured during the flight. Their was marginal operation on-board potable water system caused by a malfunctioning fuel cell. Work and rest cycles by the crew were altered to maximize the scientific data acquisition. Inadequate time was allocated for food preparation and consumption. There was low water intake by the crew because of the water shortage.
IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830
As increasing pressures of population growth and climate change arise, water and power systems (WPS) are becoming increasingly interdependent. This interdependency has resulted in an increased potential for cascading failures, whereby the service interruption of one system can propagate to interdependent ones. This paper makes four contributions. First, we present an extensive literature review in the field of integrated water and power resilience, leveraging both institutional and technical literature research landscapes. We compare various modeling approaches used to model interdependent WPS and discuss the different metrics and definitions that are typically employed to quantify and define resilience. Relevant challenges and gaps related to modeling tools and metrics are also discussed, and appropriate recommendations are made. Second, the paper presents a visualization prototype for interdependent WPS to showcase water and power system interdependencies and reveal co-managed resilience strategies that can be used to improve resilience under different types of common threats. Third, we provide a conceptual decision support framework that simultaneously optimizes a portfolio of co-managed resilience strategies in the face of multiple, uncertain threats and addresses WPS interdependencies. Finally, we present future trends regarding digitalization, integrated planning, collaborative governance, and equity needs for building more resilient WPS.
The plans, specifications, cost trade studies, and verification status of a prototype solar heating and hot water system for the Minnesota Department of Natural Resources's single-family dwelling located at O'Brien State Park, 30 miles east of Minneapolis, Minnesota are presented.
Groundwater quality is often evaluated using microbial indicators. This study examines data from 12 international groundwater studies (conducted 1992–2013) of 718 public drinking-water systems located in a range of hydrogeological settings. Focus was on testing the value of indicator organisms for identifying virus-contaminated wells. One or more indicators and viruses were present in 37 and 15% of 2,273 samples and 44 and 27% of 746 wells, respectively. Escherichia coli ( E. coli ) and somatic coliphage are 7– 9 times more likely to be associated with culturable viruspositive samples when the indicator is present versus when it is absent, while F-specific and somatic coliphages are 8–9 times more likely to be associated with culturable viruspositive wells. However, single indicators are only marginally associated with viruses detected by molecular methods, and all microbial indicators have low sensitivity and positive predictive values for virus occurrence, whether by culturable or molecular assays, i.e., indicators are often absent when viruses are present and the indicators have a high false-positive rate. Wells were divided into three susceptibility subsets based on presence of (1) total coliform bacteria or (2) multiple indicators, or (3) location of wells in karst, fractured bedrock, or gravel/cobble settings. Better associations of some indicators with viruses were observed for (1) and (3). Findings indicate the best indicators are E. coli or somatic coliphage, although both indicators may underestimate virus occurrence. Repeat sampling for indicators improves evaluation of the potential for viral contamination in a well.
The National Aeronautics and Space Administration (NASA) has used iodination as a method of microbial disinfection of potable water systems in United States spacecraft and long-duration habitability modules. A review of the effects on the thyroid following consumption o iodinated water by NASA astronauts was conducted. Pharmacological doses of iodine consumed by astronauts transiently decreased thyroid function, as reflected in serum TSH values. Although the adverse effects of excess iodine consumption in susceptible individuals are well documented, exposure to high doses of iodine during space flight did not result in a statistically significant increase in long-term thyroid disease in the astronaut population.
Zero power wireless sensors, devices, and systems are used for crop water content monitoring. The sensors consume no power while monitoring for the presence of dry crop conditions. Infrared reflectance from plants is measured and when selected spectral conditions are met, a circuit is closed, activating an alarm, an RFID tag, or a radio transmitter. The deployed sensors consume no power while monitoring, reducing or eliminating the need to change batteries.
Graphene quantum dots/Mn-N-TiO 2 /g-C 3 N 4 (GQDs/TCN) composite photocatalysts have been designed, synthesized and characterized by XRD, SEM, TEM, Raman, BET, and XPS. The photodegradation of organic pollutants (p-nitrophenol, diethyl phthalate and ciprofloxacin, called as 4-NP, CIP and DEP, respectively) coupled with simultaneous photocatalytic production of hydrogen was successfully achieved using the GQDs/TCN catalysts. The 5%GQDs/TCN-0.4 sample shows the best photocatalytic hydrogen production and organic pollutant degradation rate under simulated solar irradiation in the simultaneous photocatalytic oxidation and reduction system. Furthermore, the photocatalytic H 2 evolution rates in the solution of 4-NP, CIP and DEP are all larger than that in pure water system over the 5%GQDs/TCN-0.4 catalyst. And the H 2 evolution rate in the solution of 4-NP is smaller than that in the solutions of CIP and DEP. Accordingly, the photodegradation rate of 4-NP is larger than that of CIP and DEP. The analyses of density functional theory and liquid chromatography mass spectrometry indicate that some photogenerated electrons were used in the photodegradation process of 4-NP but not in that of CIP and DEP. And it leads to the photocatalytic rate of H 2 evolution in the 4-NP solution smaller than that in the solution of CIP and DEP. For the first time, the present work illuminates the photocatalytic enhancement of the GQDs/TCN-0.4 catalyst and the mechanism of the effect of different organic pollutants on photocatalytic H 2 evolution.
Abstract In the carbonate-water system, at equilibrium, the oxygen isotopic composition of carbonate is dependent not only on the temperature but also on the isotopic composition of host water in which the carbonate is formed. In this study, lake surface sediment and water samples were collected from 33 terminal lakes in Western China to evaluate controls on the oxygen isotopic composition of lacustrine authigenic carbonates (δ 18 O carb ) and its spatial distribution. Our results show that water oxygen isotopic composition (δ 18 O water ) rather than lake summer water temperature (T water ), is the main determinant of δ 18 O carb , irrespective of whether oxygen isotope equilibrium is achieved. There are significant linear correlations between δ 18 O carb and elevation, as well as that between δ 18 O carb and latitude for lakes located on the Tibetan Plateau. In Western China, the spatial distribution of δ 18 O carb is consistent with that of δ 18 O water , and is ultimately controlled by the isotopic composition of local precipitation (δ 18 O precipitation ) that depends on the source of water vapor. Therefore, changes in δ 18 O carb can be predominantly interpreted as variations of δ 18 O water , which in turn represent changes in δ 18 O precipitation for paleoclimate reconstructions in this region, and may be relevant to studies of other areas.
Experimental water droplet impingement data are used to validate particle trajectory computer codes used in the analysis and certification of aircraft de-icing/anti-icing systems. Water droplet impingement characteristics of aerodynamic surfaces are usually obtained from wind-tunnel dye tracer experiments. This paper presents a dye tracer method for measuring water droplet impingement characteristics on arbitrary geometries and a new data reduction method, based on laser reflectance measurements, for extracting impingement data. Extraction of impingement data has been a very time-consuming process in the past. The new data reduction method developed is at least an order of magnitude more efficient than the method previously used. The accuracy of the method is discussed and results obtained are presented.
Since March 2010 the preliminary design of the ITER ICRF Antennas have been developed by CYCLE, a consortium consisting of IPP (Garching), CCFE (Culham), CEA (Cadarache), Politecnico di Torino (Torino) and LPPERM/KMS (Brussels). This paper describes the steps taken to develop the present geometry of the triplet pair Strap Housing Module from a thermal and structural perspective, and shows the critical areas of the structure. Key issues are the manufacturability, (achieved by HIPing - Hot Isostatic Pressing), the ability to handle the radiating plasma thermal flux of 0.35 MW/m{sup 2}, the RF losses and the neutronic radiation. HIPing is necessary to achieve the complicated system of cooling channels inside the structure, which divides the coolant equally in order to supply each strap in the triplet with 1 l/s of water. The components have also to withstand the strong mechanical forces generated by plasma disruptions affecting all internal structures and the elevated design cooling water pressure of 5MPa. In order to maximise reliability, joints between different materials in the cooling water system have been kept to a minimum. Therefore, in the interests of fabricability and availability, the whole structure is manufactured out of stainless steel (316L(N)IG). The low conductivity of 316L(N)IG demands small wall thicknesses to avoid hot spots; however this reduces the mechanical strength. Consequently an in depth FEM analysis is presented, which was used to find and to improve the critical aspects of this important component and was the best means of finding the optimum between thermal and mechanical performance.
This paper evaluates the use of precipitable water (PW) from Global Positioning System (GPS) in lightning prediction. Additional independent verification of an earlier model is performed. This earlier model used binary logistic regression with the following four predictor variables optimally selected from a candidate list of 23 candidate predictors: the current precipitable water value for a given time of the day, the change in GPS-PW over the past 9 hours, the KIndex, and the electric field mill value. This earlier model was not optimized for any specific forecast interval, but showed promise for 6 hour and 1.5 hour forecasts. Two new models were developed and verified. These new models were optimized for two operationally significant forecast intervals. The first model was optimized for the 0.5 hour lightning advisories issued by the 45th Weather Squadron. An additional 1.5 hours was allowed for sensor dwell, communication, calculation, analysis, and advisory decision by the forecaster. Therefore the 0.5 hour advisory model became a 2 hour forecast model for lightning within the 45th Weather Squadron advisory areas. The second model was optimized for major ground processing operations supported by the 45th Weather Squadron, which can require lightning forecasts with a lead-time of up to 7.5 hours. Using the same 1.5 lag as in the other new model, this became a 9 hour forecast model for lightning within 37 km (20 NM)) of the 45th Weather Squadron advisory areas. The two new models were built using binary logistic regression from a list of 26 candidate predictor variables: the current GPS-PW value, the change of GPS-PW over 0.5 hour increments from 0.5 to 12 hours, and the K-index. The new 2 hour model found the following for predictors to be statistically significant, listed in decreasing order of contribution to the forecast: the 0.5 hour change in GPS-PW, the 7.5 hour change in GPS-PW, the current GPS-PW value, and the KIndex. The new 9 hour forecast model found the following five independent variables to be statistically significant, listed in decreasing order of contribution to the forecast: the current GPSPW value, the 8.5 hour change in GPS-PW, the 3.5 hour change in GPS-PW, the 12 hour change in GPS-PW, and the K-Index. In both models, the GPS-PW parameters had better correlation to the lightning forecast than the K-Index, a widely used thunderstorm index. Possible future improvements to this study are discussed.
Minerals found in playa evaporite deposits reflect the chemically diverse origins of ground waters in arid regions. Recently, it was discovered that many playa minerals exhibit diagnostic visible and near-infrared (0.4-2.5 micron) absorption bands that provide a remote sensing basis for observing important compositional details of desert ground water systems. The study of such systems is relevant to understanding solute acquisition, transport, and fractionation processes that are active in the subsurface. Observations of playa evaporites may also be useful for monitoring the hydrologic response of desert basins to changing climatic conditions on regional and global scales. Ongoing work using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to map evaporite minerals in the Death Valley salt pan is described. The AVIRIS data point to differences in inflow water chemistry in different parts of the Death Valley playa system and have led to the discovery of at least two new North American mineral occurrences. Seven segments of AVIRIS data were acquired over Death Valley on 31 July 1990, and were calibrated to reflectance by using the spectrum of a uniform area of alluvium near the salt pan. The calibrated data were subsequently analyzed by using least-squares spectral band-fitting methods, first described by Clark and others. In the band-fitting procedure, AVIRIS spectra are fit compared over selected wavelength intervals to a series of library reference spectra. Output images showing the degree of fit, band depth, and fit times the band depth are generated for each reference spectrum. The reference spectra used in the study included laboratory data for 35 pure evaporite spectra extracted from the AVIRIS image cube. Additional details of the band-fitting technique are provided by Clark and others elsewhere in this volume.