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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Fleet-wide Electrification Impacts Assessment for the Valley Transportation Authority

This report explores the long-term electrification opportunities for the Valley Transit Authority’s (VTA) transit bus fleet. The potential for transit bus electrification at VTA as well as the economic impacts of partial and complete electrification are explored. We use the Revenue Operation and Device Optimization model to determine the optimal charging, operation and lowest capital and operating cost solution to achieve different levels of electrification to meet their existing routes. This study finds that, relying on only depot charging, around 70% of the daily trips by VTA’s transit bus fleet can be replaced with battery electric buses (BEBs) today. The benefits and drawbacks of five methods for improving the electrification potential beyond that achievable with only depot charging are discussed including (1) increase charger power, (2) purchase of larger vehicle batteries, (3) en-route charging, (4) purchasing additional buses and swapping them to enable the existing routes/blocks1 to be met, and (5) route/block redesign. A strategy is developed to enable full fleet electrification by increasing charger power or allowing intraday charging as a proxy for the options mentioned above. This method allows us to develop an understanding of the impacts and trade-offs of full fleet electrification. Two charging strategies are examined. Immediate charging, when the bus is charged as soon as it arrives at a depot or en-route charging station, and smart charging, which uses a controller to determine the best times to charge to achieve the lowest charging cost, while maintaining the same trip schedules. Smart charging is effective at reducing the peak power consumption, which can be reduced by between 31% and 65% compared to immediate charging. This translates directly to lower electricity demand charges and lower costs for possible distribution system upgrades. The total lifetime net present value (NPV) costs for different scenarios are presented in Figure ES-1. Scenarios are separated into three sections. The first stacked bar on the left is the base case (business-as-usual) where all buses are diesel hybrids, the next four bars include partial and full fleet electrification utilizing only immediate charging, and the last four bars include partial and full fleet electrification utilizing smart charging. The results show that smart charging scenarios are within ±4% of the lifetime NPV cost of the diesel-hybrid only (business-as-usual) scenario. The scenarios with full fleet electrification (i.e., including intraday charging) are 4% lower cost and those with partial fleet electrification (i.e., without intraday charging) are 2%–3% higher. However, it is important to note that the intraday charging scenarios do not include any additional costs for the equipment necessary to achieve intraday charging (e.g., additional chargers, larger batteries, new route design). Additionally, it is worth noting that the Low Carbon Fuel Standard (LCFS) credit received for implementing electric buses is essential to achieving these results.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Adaptive Neurocontrol for Grid-Following Inverters

The new generation of power systems involve a large number of autonomous operating units with the flow of data being restricted by privacy concerns or infrastructure hurdles. The systems are also time-varying so the control should adjust in a timely manner to avoid failures that usually have very negative economical implications. Adaptive neurocontrol which takes elements from adaptive control (great for time-varying problems) and model identification (could be in the form of neural network) by using local available data is a compelling tool. In this work, we summarize analytical results for adaptive neurocontrol, followed with numerical verification of how the method could work for future grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels: 2022 State of Technology

Data from Pacific Northwest National Laboratory’s (PNNL) conversion hydrothermal liquefaction (HTL) program for wet waste was used to update the pathway techno-economic analysis (TEA) for the fiscal year 2022 State of Technology (2022 SOT). Figure S.1 shows the modeled minimum fuel selling price (MFSP) for the 2022 SOT, along with the previous years’ SOTs (Snowden-Swan et al. 2020, 2021, 2022). These costs are for a HTL plant scale of 110 dry ton/day sludge feed and a larger centralized upgrading plant scale of 38 million gallons/year biocrude feed, commensurate with the design case. All costs were updated to 2020 dollars. Corresponding cost breakdowns and technical parameters for each case are given in Appendix B. In previous years’ analyses options with and without ammonia (NH 3 ) stripping treatment of the HTL aqueous phase recycle stream were included in the analysis to account for cases with direct recycle of untreated HTL aqueous phase back to the wastewater treatment plant. In the FY21 SOT assessment however, system boundaries for the analysis were adjusted to reflect separate ownership/operatorship for the HTL plant and with that, nutrient surcharge fees associated with disposal of the aqueous phase wastewater to a municipal sewer system were incorporated to provide an improved accounting of true disposal costs for a standalone plant. With these changes, there is no significant cost difference between the case including ammonia removal and the case excluding ammonia removal and therefore the “no NH3 removal” options will not be included in the 2022 and future SOTs.

09 BIOMASS FUELS↗
DOE OSTI2024

Development and Experimental Optimization of High-Temperature Modeling Tools and Methods for Concentrated Solar Power Particle - Systems

A novel, open-source radiative modeling toolset was developed to extend the functionality of particle-based modeling software (e.g. discrete element method (DEM)) to environmental conditions relevant to concentrated solar power applications. This toolset was optimized for deployment on desktop workstations instead of high-performance computing systems, to render such tools more accessible to the research community. Both particle-based modeling and radiative exchange modeling are computationally expensive and often require specialized programming expertise, making these methods cumbersome to use. Recent developments in DEM software by DCS Computing have greatly reduced these challenges, providing a graphical-user-interface based platform and modeling optimization for desktop workstations, HPCs, and cloud computing. The University of Dayton leveraged the experience of DCS Computing in developing a user-friendly, open-source radiative heat transfer expansion for DEM modeling. The University of Dayton DEM+ radiative modeling toolset was developed using a combination of fundamental experimental measurements, modeling, and simplified flow experiments over a range of temperatures and flow conditions. The toolset provides researchers with access to multiple radiative models including an accelerated Monte-Carlo Ray Tracing (application agnostic, highly computationally expensive), an expanded database of distance-based approximations (application limited, computationally light), and a weighted blending of the two methods capable of achieving over 90% reduction in computation time with equivalent accuracy compared to Monte-Carlo Ray Tracing. Through a graphical user interface, users can customize the radiative models to match their desired accuracy and available computational resources, improving access to particle based modeling for the research community. Ceramic sintered bauxite proppants were used in modeling and experimentally as a baseline. Both the radiative heat transfer and flow properties for particulate systems were investigated at elevated temperatures up to 800 °C. The major accomplishments for this work include a verified, open-source radiative modeling toolset to be distributed amongst the research community and the fabrication of three small-scale test facilities to investigate particle behavior and tune DEM flow properties for operation up to 800 °C. The findings have been shared with the research community via conference modeling workshops, deployment of the tools in DCS Computing Aspherix®, and open-source access to the developed radiative modeling tool. The development of next-generation CSP facilities and thermal energy storage systems based on ceramic particles requires providing access to computationally efficient and accurate modeling tools. Particles will experience a wide range of environments (20-800 °C) and handling conditions (dilute curtains or dense packing), requiring specially designed and optimized equipment. Optimizing solid particle physics models and establishing best-practices for particle modeling in CSP environments will assist researchers with designing optimized equipment, accelerating the deployment of more economically-competitive CSP facilities.

14 SOLAR ENERGY↗
NASA NTRS1972

Digital controller for high pressure rocket engine.

Description of a general approach for the design of an adaptive digital control system for liquid bipropellant rocket engines. The technique employs linearized transfer functions derived from perturbations of an engine simulation. The linear models serve as a basis on which to develop candidate closed-loop control laws quickly and economically.

Thompson, Z.↗
NASA NTRS1978

A maintenance model for k-out-of-n subsystems aboard a fleet of advanced commercial aircraft

Proposed highly reliable fault-tolerant reconfigurable digital control systems for a future generation of commercial aircraft consist of several k-out-of-n subsystems. Each of these flight-critical subsystems will consist of n identical components, k of which must be functioning properly in order for the aircraft to be dispatched. Failed components are recoverable; they are repaired in a shop. Spares are inventoried at a main base where they may be substituted for failed components on planes during layovers. Penalties are assessed when failure of a k-out-of-n subsystem causes a dispatch cancellation or delay. A maintenance model for a fleet of aircraft with such control systems is presented. The goals are to demonstrate economic feasibility and to optimize.

Miller, D. R.↗
NASA NTRS1982

ID wafering technology

Improvements in ID saws leading to lower costs for producing silicon wafers for solar cells are described. The relationships between crystal size and blade size and between the length of time it takes to slice a wafer and wafer thickness are discussed. The influence of ingot production methods on wafering performance is considered. A cost sensitivity analysis of slicing a 10 cm square ingot and economic analyses of slicing a four inch and a six inch ingot are presented. A wafering cost model based on the IPEG 2 is given.

Aharonyan, P.↗
NASA NTRS1983

Customer premises services market demand assessment 1980 - 2000: Volume 2

Potential customer premises service (CPS), telecommunication services, potential CPS user classes, a primary research survey, comparative economics, market demand forcasts, distance distribution of traffic, segmentation of market demand, and a nationwide traffic distribution model are discussed.

Gamble, R. B.↗
NASA NTRS1985

Study for the optimization of a transport aircraft wing for maximum fuel efficiency. Volume 1: Methodology, criteria, aeroelastic model definition and results

Work performed in the design of a transport aircraft wing for maximum fuel efficiency is documented with emphasis on design criteria, design methodology, and three design configurations. The design database includes complete finite element model description, sizing data, geometry data, loads data, and inertial data. A design process which satisfies the economics and practical aspects of a real design is illustrated. The cooperative study relationship between the contractor and NASA during the course of the contract is also discussed.

Radovcich, N. A.↗
NASA NTRS2002

System Level Uncertainty Assessment for Collaborative RLV Design

A collaborative design process utilizing Probabilistic Data Assessment (PDA) is showcased. Given the limitation of financial resources by both the government and industry, strategic decision makers need more than just traditional point designs, they need to be aware of the likelihood of these future designs to meet their objectives. This uncertainty, an ever-present character in the design process, can be embraced through a probabilistic design environment. A conceptual design process is presented that encapsulates the major engineering disciplines for a Third Generation Reusable Launch Vehicle (RLV). Toolsets consist of aerospace industry standard tools in disciplines such as trajectory, propulsion, mass properties, cost, operations, safety, and economics. Variations of the design process are presented that use different fidelities of tools. The disciplinary engineering models are used in a collaborative engineering framework utilizing Phoenix Integration's ModelCenter and AnalysisServer environment. These tools allow the designer to join disparate models and simulations together in a unified environment wherein each discipline can interact with any other discipline. The design process also uses probabilistic methods to generate the system level output metrics of interest for a RLV conceptual design. The specific system being examined is the Advanced Concept Rocket Engine 92 (ACRE-92) RLV. Previous experience and knowledge (in terms of input uncertainty distributions from experts and modeling and simulation codes) can be coupled with Monte Carlo processes to best predict the chances of program success.

Charania, A. C.↗
DOE OSTI2022

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗
NASA NTRS2003

Small Aircraft Transportation System Simulation Analysis of the HVO and ERO Concepts

It is acknowledged that the aviation and aerospace industries are primary forces influencing the industrial development and economic well being of the United States and many countries around the world. For decades the US national air transportation system has been the model of success - safely and efficiently moving people, cargo, goods and services and generating countless benefits throughout the global community; however, the finite nature of the system and many of its components is becoming apparent. Without measurable increases in the capacity of the national air transportation system, delays and service delivery failures will eventually become intolerable. Although the recent economic slowdown has lowered immediate travel demands, that trend is reversing and cargo movement remains high. Research data indicates a conservative 2.5-3.0% annual increase in aircraft operations nationwide through 2017. Such growth will place additional strains upon a system already experiencing capacity constraints. The stakeholders of the system will continue to endure ever-increasing delays and abide lesser levels of service to many lower population density areas of the country unless more efficient uses of existing and new transportation resources are implemented. NASA s Small Aircraft Transportation System program (SATS) is one of several technologies under development that are aimed at using such resources more effectively. As part of this development effort, this report is the first in a series outlining the findings and recommendations resulting from a comprehensive program of multi-level analyses and system engineering efforts undertaken by NASA Langley Research Center s Systems Analysis Branch (SAB). These efforts are guided by a commitment to provide systems-level analysis support for the SATS program. Subsequent efforts will build upon this early work to produce additional analyses and benefits studies needed to provide the technical and economic basis for national investment and policy decisions related to further development and potential deployment of a small aircraft transportation system. This report primarily serves two purposes. First, it presents results attained from an initial evaluation and analysis of the Higher Volume Operations (HVO) and EnRoute Operations (ERO) concepts - both designated operational capabilities within the SATS Program s Concept of Operations (CONOPS) document. It further outlines areas of the concepts that would benefit from follow-on analyses and system engineering efforts. It is intended that these processes will aid continued maturation of the concepts and promote additional studies of their effects and influences in combination with other designated CONOPS currently under development. In essence, it establishes a baseline of data upon which subsequent analyses and studies can be built and identifies performance characteristics the concept must exhibit in order to provide, at minimum, levels of safety and usage equal to or better than the current system.

Millsaps, Gary D.↗
NASA NTRS2024

Fault Diagnosis of Power Components with Reliability Assessment in Extraterrestrial Microgrids

This research investigates the possible failures caused by aging and other environmental and external factors that could significantly impact the performance of extraterrestrial power systems. Additionally, it presents a reliability assessment model for the space microgrid based on fault tree analysis (FTA). The reliability assessment model developed in this paper represents a tool that can be used by engineers to harden the system design for operational and economic benefits. To improve the reliability of the system, this work provides a broad review of the different fault detection and diagnosis (FDD) algorithms used for power microgrids and space applications. Using data sets from the Habitat Simulator developed through the NASA-funded Resilient Extraterrestrial Habitat Institute, this paper compares the applicability and accuracy of the different FDD methods. The primary FDD approach proposed and assessed in this work is based on the Markov reliability model. It predicts and detects future faults in the space microgrids by using past data samples and categorizing them into different classes. Data-driven-based models such as artificial neural networks are also investigated, tested, and evaluated using simulation data sets. According to the simulation results and the broad FDD algorithm comparison, this study provides the crew or maintenance engineers with a clear methodology to detect and localize power system failures.

Leila Chebbo↗
DOE OSTI2024

Effects of the U.S. inflation reduction act on SMR economics

The U.S. Inflation Reduction Act (IRA) of 2022 provides a wide array of tax credits and other incentives for low-carbon energy. The technology-neutral clean generation production tax credit (PTC) (Section 45Y of the U.S. Internal Revenue Code) and the technology-neutral investment tax credit (ITC) (Section 48E) lower the net cost of new electricity generation projects with zero or negative greenhouse gas emission rates. We evaluate the impact of the IRA legislation—specifically the PTC and ITC—on the cost-competitiveness of small modular reactors (SMRs). We use the Argonne Low-carbon Energy Analysis Framework (A-LEAF) model to calculate the capacity factor of an SMR with a range of hypothetical variable operating and maintenance (O&M) costs in the Electric Reliability Council of Texas (ERCOT) electricity market. We selected ERCOT for market modeling because of its competitive structure, available data, and extensive use in prior literature. We use a discounted cash flow model to calculate the SMR’s net present value based on the market prices and capacity factors from A-LEAF, hypothetical ranges of capital and variable O&M costs, and other input parameters, with or without the IRA tax credits. We determine the SMR owner’s optimal choice of PTC or ITC for the hypothetical ranges of capital and variable O&M costs. We also evaluate potential shifts in the SMR owner’s optimal choice of PTC or ITC based on historical patterns of nuclear capital cost overruns in the United States. We also assess the sensitivity of our results to longer PTC period and electricity prices from the New England market, which tend to be higher than electricity prices in ERCOT. We find that even with the IRA tax credits, only SMRs with low capital and variable O&M costs would be economically feasible in the low-price ERCOT market scenario modeled. A longer PTC period and higher-price market such as New England, however, would significantly expand the economic feasibility of SMRs in the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2006

System Architecture Modeling for Technology Portfolio Management using ATLAS

Strategic planners and technology portfolio managers have traditionally relied on consensus-based tools, such as Analytical Hierarchy Process (AHP) and Quality Function Deployment (QFD) in planning the funding of technology development. While useful to a certain extent, these tools are limited in the ability to fully quantify the impact of a technology choice on system mass, system reliability, project schedule, and lifecycle cost. The Advanced Technology Lifecycle Analysis System (ATLAS) aims to provide strategic planners a decision support tool for analyzing technology selections within a Space Exploration Architecture (SEA). Using ATLAS, strategic planners can select physics-based system models from a library, configure the systems with technologies and performance parameters, and plan the deployment of a SEA. Key parameters for current and future technologies have been collected from subject-matter experts and other documented sources in the Technology Tool Box (TTB). ATLAS can be used to compare the technical feasibility and economic viability of a set of technology choices for one SEA, and compare it against another set of technology choices or another SEA. System architecture modeling in ATLAS is a multi-step process. First, the modeler defines the system level requirements. Second, the modeler identifies technologies of interest whose impact on an SEA. Third, the system modeling team creates models of architecture elements (e.g. launch vehicles, in-space transfer vehicles, crew vehicles) if they are not already in the model library. Finally, the architecture modeler develops a script for the ATLAS tool to run, and the results for comparison are generated.

Thompson, Robert W.↗
NASA NTRS2017

Building an Economical and Sustainable Lunar Infrastructure to Enable Lunar Industrialization

A new concept study was initiated to examine the architecture needed to gradually develop an economical, evolvable and sustainable lunar infrastructure using a public/private partnerships approach. This approach would establish partnership agreements between NASA and industry teams to develop a lunar infrastructure system that would be mutually beneficial. This approach would also require NASA and its industry partners to share costs in the development phase and then transfer operation of these infrastructure services back to its industry owners in the execution phase. These infrastructure services may include but are not limited to the following: lunar cargo transportation, power stations, communication towers and satellites, autonomous rover operations, landing pads and resource extraction operations. The public/private partnerships approach used in this study leveraged best practices from NASA's Commercial Orbital Transportation Services (COTS) program which introduced an innovative and economical approach for partnering with industry to develop commercial cargo services to the International Space Station. This program was planned together with the ISS Commercial Resupply Services (CRS) contracts which was responsible for initiating commercial cargo delivery services to the ISS for the first time. The public/private partnerships approach undertaken in the COTS program proved to be very successful in dramatically reducing development costs for these ISS cargo delivery services as well as substantially reducing operational costs. To continue on this successful path towards installing economical infrastructure services for LEO and beyond, this new study, named Lunar COTS (Commercial Operations and Transport Services), was conducted to examine extending the NASA COTS model to cis-lunar space and the lunar surface. The goals of the Lunar COTS concept are to: 1) develop and demonstrate affordable and commercial cis-lunar and surface capabilities, such as lunar cargo delivery and surface power generation, in partnership with industry; 2) incentivize industry to establish economical and sustainable lunar infrastructure services to support NASA missions and initiate lunar commerce; and 3) encourage creation of new space markets for economic growth and benefit. A phased-development approach was also studied to allow for incremental development and demonstration of capabilities needed to build a lunar infrastructure. This paper will describe the Lunar COTS concept goals, objectives and approach for building an economical and sustainable lunar infrastructure. It will also describe the technical challenges and advantages of developing and operating each infrastructure element. It will also describe the potential benefits and progress that can be accomplished in the initial phase of this Lunar COTS approach. Finally, the paper will also look forward to the potential of a robust lunar industrialization environment and its potential effect on the next 50 years of space exploration.

Zuniga, Allison F.↗
DOE OSTI2022

Mechanistic insights into metal, nitrogen doped carbon catalysts for oxygen reduction: progress in computational modeling

We report metal and nitrogen doped carbon materials (denoted as M–N–C) synthesized through high-temperature pyrolysis have been found to exhibit activity for oxygen reduction reaction (ORR) approaching that of Pt and electrochemical stability higher than previous MN 4 -containing macrocyclic molecular catalysts. Tremendous efforts have thus been devoted to the advancement of M–N–C catalysts as an economical alternative to Pt-based catalysts for proton exchange membrane fuel cell cathodes with a focus on simultaneously improving activity and stability. To this end, novel computational modeling techniques have been developed and applied to acquire knowledge crucial for accelerating the pace of M–N–C catalyst development. In this review, recent progress in computational method development, as well as the predictions of chemical structure of active sites, reaction pathways, ORR kinetics, and catalyst stability in electrochemical environments, are critically surveyed. Moreover, the crucial role of computational modeling to elucidate the functional mechanism of M–N–C catalysts for ORR in acid media and enable rational design of M–N–C catalysts is discussed with a visionary outlook for the field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

An Integrated Feasibility Study of Reservoir Thermal Energy Storage (RTES) in Portland, OR, USA

In regions with long cold overcast winters and sunny summers, Deep Direct-Use (DDU) can be coupled with Reservoir Thermal Energy Storage (RTES) technology to take advantage of pre-existing subsurface permeability to save summer heat for later use during cold seasons. Many aquifers worldwide are underlain by permeable regions (reservoirs) containing brackish or saline groundwater that has limited beneficial use due to poor water quality. We investigate the utility of these relatively deep, slow flowing reservoirs for RTES by conducting an integrated feasibility study in the Portland Basin, Oregon, USA, developing methods and obtaining results that can be widely applied to RTES systems elsewhere. As a case study, we have conducted an economic and social cost-benefit analysis for the Oregon Health and Science University (OHSU), a teaching hospital that is recognized as critical infrastructure in the Portland Metropolitan Area. Our investigation covers key factors that influence feasibility including 1) the geologic framework, 2) heat and fluid flow modeling, 3) capital and maintenance costs, 4) the regulatory framework, and 5) operational risks. By pairing a model of building seasonal heat demand with an integrated model of RTES resource supply, we determine that the most important factors that influence RTES efficacy in the study area are operational schedule, well spacing, the amount of summer heat stored (in our model, a function of solar array size), and longevity of the system. Generally, heat recovery efficiency increases as the reservoir and surrounding rocks warm, making RTES more economical with time. Selecting a base-case scenario, we estimate a levelized cost of heat (LCOH) to compare with other sources of heating available to OHSU and find that it is comparable to unsubsidized solar and nuclear, but more expensive than natural gas. Additional benefits of RTES include energy resiliency in the event that conventional energy supplies are disrupted (e.g., natural disaster) and a reduction in fossil fuel consumption resulting in a smaller carbon footprint. Key risks include reservoir heterogeneity and a possible reduction in permeability through time due to scaling (mineral precipitation). Lastly, a map of thermal energy storage capacity for the Portland Basin yields a total of 43,400 GWh, suggesting tremendous potential for RTES in the Portland Metropolitan Area.

14 SOLAR ENERGY↗