Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “PROSPECT”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

BETO 2021 Peer Review - WBS 4.1.2.32: Bioeconomy Scenario Analysis

The Bioeconomy Scenario Analysis project uses systems thinking and analysis to assess current and/or prospective techno-economics, research and development, deployment strategies, policy, and market conditions and their impact on the potential development trajectories of the bioenergy industry over time. Results from this project include identification of opportunities and constraints to industrial development, quantification of multiple metrics (energy, economic, environmental) and informing researchers, decision makers, and industry of the steps needed for a sustainable, nationwide biofuels industry. Analyses from this project enable the creation of a bioenergy industry by (1) inciting policy-makers to explore scenarios for nationwide biofuels production, identifying policy actions consistent with pathways for growth; (2) improving industry’s understanding of industry growth potential under different technology and investment conditions, better targeting their development efforts; and (3) providing universities and other interested stakeholders with tools and analyses that can be adapted to meet research and teaching objectives, connecting students with careers that build the industry. One of the many modeling tools used in this project, the Biomass Scenario Model (BSM) is a publicly-available, unique, validated, state-of-the-art, award-winning, fourth-generation model of the domestic biofuels supply chain which explicitly focuses on how and under what conditions biofuel technologies might be deployed to contribute to the U.S. transportation energy sector. We use models like the BSM to examine the implications of policies and incentives as well as their potential side-effects. The BSM uses a system-dynamics simulation to model dynamic interactions and transitions across the supply chain; it tracks the deployment of biofuels given industrial learning and the reaction of the investment community in the context of land availability, projected oil markets, consumer demand for biofuels, and government policies over time. Under expected market conditions, analyses using the BSM suggest that the biofuels industry may require significant external actions in the early years to thrive. Interventions that accelerate the industrial learning process (e.g. operation of pre-commercial and commercial facilities) have been identified as having strong influence in starting the growth of a commercial biofuel industry. Policies which are coordinated across the whole supply chain in BSM foster the growth of the biofuels industry and production of tens of billions of gallons of biofuels may occur under sufficiently favorable conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Opportunities to Enable Electrolytic H2 Projects for Ammonia in the United States

Integration of large-scale electrolysis with the grid provides value to hydrogen and ammonia markets as well as the electricity system. Electrolysis has the potential to provide an alternative source of low-cost hydrogen by utilizing low-price electricity that may have limited availability, resulting in possible economic benefits for ammonia production. The use of that low-price electricity can simultaneously benefit the grid by reducing the price suppression that may occur with increased penetration of variable renewable generation. In addition, the rapid-response characteristics of electrolyzers enables them to provide ancillary services to the grid, such as operating reserves and frequency control. However, electrolyzer capital cost reductions, favorable electricity pricing structures, or other technology or market advancements are likely needed to achieve hydrogen prices competitive with incumbent production technologies. We discuss near-term, niche prospects where low-cost electrolytic hydrogen and ammonia could be produced, possible applications for those products, and further opportunities and drivers that might enable them.

39 EE - Hydrogen and Fuel Cell Technologies (EE-3F↗
DOE OSTI2021

THERMAL/STRUCTURAL ANALYSIS OF THE AXION QUANTUM METROLOGY CAVITY AND ITS COMPONENTS

This research was centered around maximizing the capability to cool dielectric material within a containment unit, or Photonic Band Gap (PBG) cavity, designed for detecting axion dark matter and identifying the unit’s thermal properties. There are multiple types of PBG cavities, but the latest version that axion researchers wish to use has been theorized to contain possible issues related to its thermal properties. Thermal conductivity is an issue with the dielectric material because it is made from alumina which is highly insulative. This is important since the research is being done in a cryogenic environment and the thermal noise affects the quantum bit used for detecting the axion to photon conversion process. Therefore, any improvements to this unit should be justified and implemented but are not entirely limited to thermal contact related aspects of PBG cavities. A prospect of using sapphire in place of alumina also exists, but this is a more expensive, less tested, and more elusive material to justify the creation of a full dielectric structure out of sapphire. Thermal aspects of the cavity were analyzed using finite element method (FEM) and an experiment designed to test different thermal joint materials. FEM was used to check the contraction of the cavity during cooling, the contact quality between the dielectric material and cavity wall, theheat flow rate through the assembly, and helps visualize the cavity’s reaction to different design changes. A simple comparison between thermal conductivity curves justified the usage of sapphire over alumina from a thermal property point of view. Thus, the method of experimentation had an additional dielectric material, sapphire, to test with and compare to alumina. The thermal test identified which material is best to use for a thermal joint but also simultaneously found the conductance of the joint and dielectric material as well as an estimate for what the temperature is inside the larger scale cavity since a thermometer cannot be placed inside the PBG when it cools. Initially, the cavity simulation was tested for structural deformation properties and stress distribution since it is made of copper which contracts heavily in comparison to most other materials. The reduction in volume of the cavity was less than anticipated which gave more room for a possible usage of a modified thermal joint for additional contact area and higher conductivity.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Combined Techno-Economic Analysis and Life Cycle Assessment of an Integrated Direct Air Capture System with Advanced Algal Biofuel Production

The continuous increase in carbon dioxide (CO2) concentration in the atmosphere since the First Industrial Revolution correlates convincingly with the ongoing rise of the Earth's global average temperature contributing to climate change. As a response, carbon capture and sequestration (CCS) technologies are being implemented to mitigate anthropogenic CO2 emissions by capturing CO2 from high emitting point sources, such as power plants, refineries, and cement factories, and subsequently buried in geological formations underground for long term storage. Recently direct air capture (DAC) has emerged as a promising alternative technology that captures CO2 directly from the atmosphere for use or sequestration. This study investigates the potential synergistic benefits of integrating a solid amine-based DAC system with advanced algal biofuel production in photobioreactors (PBRs). DAC utilization allows the removal of atmospheric CO2 while also decoupling algae production facilities from anthropogenic point CO2 sources and avoiding the cost and logistics challenges of transporting CO2 long distances to remote facilities. Techno-economic analysis and life cycle assessment are performed to assess the economic and environmental benefits of heat and mass integration between the DAC and the PBR for biofuel production. The DAC-PBR system integration also considers on-site flue gas handling options, DAC capital utilization, the tradeoff between centralization or decentralization of key unit operations, and the PBR array. This presentation will discuss how optimizing DAC-PBR process integration can enhance the algal biofuel's economic and environmental sustainability and the prospect of DAC enabling the circular carbon economy.

algal biofuel production↗
DOE OSTI2021

Strategic Trade Atlas 2015-2019: Country- and Commodity-Based Views

A Strategic Trade Atlas was developed to promote understanding of global trade flows of strategic goods, i.e., goods of militarily strategic value, including dual-use goods. This Atlas provides macroscopic graphical representations of global trade flows classified under Harmonized System (HS) codes associated by the World Customs Organization with strategic commodities. The profiles provide information rich representations of strategic commodity-related imports and exports classified under these HS codes, based on data originally reported to and made publicly available by the United Nations Statistical Division, then processed to reconcile trade asymmetries by the Centre d'Etudes Prospectives et d'Informations Internationales. This and other high quality, statistically relevant data sources exist, but are largely untapped resources for strategic trade control purposes. Efforts to promote and facilitate use of trade data should enhance the effectiveness and efficiency of strategic trade control efforts.

strategic trade, world customs organization, trade↗
DOE OSTI2021

Analysis of Selected Publicly Available Geothermal Exploration Data Gaps

As part of a United States Department of Energy (DOE) supported retrospective analysis of DOE's Play Fairway Analysis (PFA) projects, the National Renewable Energy Laboratory (NREL) compiled and analyzed publicly available geothermal exploration datasets to identify and highlight data gaps in areas prospective for hosting geothermal resources. The analysis was intended to understand the existing geographic coverage of selected datasets commonly utilized both by the PFA projects and geothermal developers during resource assessments including geologic mapping, temperature gradient drilling, and aeromagnetic, gravimetric, and lidar surveys. Results indicate that broad areas of the western United States estimated to have geothermal potential lack sufficient geologic and geophysical coverage necessary for even regional resource exploration. The study directly informed the recent Geoscience Data Acquisition for Western Nevada, or GeoDAWN - which united DOE's Geothermal Technologies Office (GTO) with the U.S. Geological Survey (USGS) of the U.S. Department of the Interior to assist U.S. needs for energy and critical minerals. The study also has the potential to inform public investment in further data acquisition for characterization of the Earth both for geothermal and other natural resource assessments.

data↗
DOE OSTI2021

Efforts and Innovations to Promote Data Sharing and Data Accessibility in the EGS Collab Experiments

Large-scale scientific research programs such as the EGS Collab experiments and the FORGE program play extremely important roles in advancing geothermal technologies. Such efforts involve a large number of researchers from multiple institutions, last multiple years, and generate large, complex datasets. The value of the research efforts is only realized when the datasets are used by a large community of researchers in the decades to come. A challenge is that due to the complexity of the data, it could require a user to devote a serious effort into understanding the data before the data can be effectively utilized. In the EGS Collab experiments, the team has devoted remarkable efforts and developed many innovative solutions to make the data more accessible to broader team members and future users. This paper documents the experience gained and lessons learned by the EGS Collab team in disseminating the data in the most informative and inspiring forms to maximize the value of this precious dataset. "Accessibility"in the title does not only mean making the raw data available for download. Particularly, we want to emphasize the importance of organizing, annotating, and presenting the data in ways to make it easy to digest by prospective consumers of the data.

circulation↗
DOE OSTI2021

Can color-mixed system technology improve lighting quality and energy efficiency?

LEDs have made tremendous inroads in the architectural lighting market but have yet to reach their potentials for energy efficiency or delivering benefit to building occupants. Progress in color-mixed systems can contribute to both goals with anticipated benefits for luminous efficacy, application efficacy, human health, plant growth, and general satisfaction. These benefits can be achieved because unlike static, broadband white light emitters that are ubiquitous today, color-mixed systems offer spectral flexibility. The prospect of widespread implementation of tunable lighting by the 2030s is exciting, but it will require overcoming several challenges and greater responsibility from the specifier. Now is the time to begin planning and developing effective strategies for deploying color-mixed LED systems. Here we examine the pros, cons, and development path for this technology.

Royer, Michael P.↗
DOE OSTI2022

4.2.1.31 Integrated Life Cycle Sustainability Analysis

This project provides the Department of Energy's Bioenergy Technologies Office (BETO) with strategic decision-support for the evaluation of its R&D portfolio by developing, validating, and applying a coherent methodology and consistent model framework to quantify the net effects of an expanding US bioeconomy. The framework fills an analysis gap previously identified by Peer Review and supports a related milestone in BETO's Multi-Year Program Plan. The framework was scoped with inputs from practitioners in academia, national laboratories, and federal agencies. The model is a top-down, economy-wide framework using a coherent methodology to compute environmental and socio-economic metrics. It is purposefully complementary to existing bottom-up, process-based techno-economic and life cycle assessment BETO tools and uses their data as inputs. Presently, the model covers several commercial and near-commercial biofuel routes and an emerging pathway for plastics upcycling. It covers temporal detail across four time-steps and is currently being expanded with a prospective modeling capability. The model has provided analyses for the Third Triennial Report to Congress (RtC3) on the environmental impacts of the Renewable Fuel Standard (RFS2), among others. As part of this project, NREL also provides scientific support to BETO in the International Energy Agency's Technology Collaboration Program on Bioenergy (IEA Bioenergy) Task 45 on Sustainability. Here, NREL evaluates and synthesizes activities that develop, compare, or apply metrics, methods, and tools to quantify sustainability effects of bioeconomy products. NREL also coordinates related national lab involvement and a BETO Working Group on Sustainable Land Management.

bioeconomy↗
DOE OSTI2022

Data Curation for Machine Learning Applied to Geothermal Power Plant Operational Data for GOOML: Geothermal Operational Optimization with Machine Learning: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach to physics-guided, data-centric machine learning. This framework has been used to develop digital twins that provide steamfield operators with operational environments to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management in real world applications. To create, test, and apply the GOOML framework, diverse time-series datasets spanning multiple years were sourced from various geothermal power plant components within several complex real-world geothermal operations. These operations are based in the United States and New Zealand and include a variety of technologies, end-uses and configurations, collectively covering nearly all relevant operating conditions for modern geothermal fields. Datasets were acquired from multiple sources to ensure that machine learning experiments generalized properly to various operating conditions. It was found that the data varied in quality, format, and completeness. To ensure consistency between the various datasets, a standardized data curation process was developed to reliably streamline data preparation. This paper will discuss best practices as learned from the GOOML data curation process which takes the following steps: 1) acquisition of large quantities of data from power plant operators, 2) digestion of data to gain an initial understanding of what is included, 3) data transformation, which includes converting the data into a standardized machine-readable format so that they can be visualized, quality checked, and cleaned, 4) quality assurance and quality control, involving identification of significant data gaps and apparent anomalies through mapping of data features to real world componentry via the GOOML historical model, followed by discussion with modelers and power plant operators to identify additional data needs and to resolve issues, 5) use in machine learning algorithms, and 6) repetition of steps one through five until all data needs are met and data are deemed suitable for producing trustworthy modeling results which may be disseminated, ideally along with the curated dataset. This iterative process is focused on improving the quality of the data rather than tuning machine learning model parameters and supports a shift towards data-centric AI as a means to improving real-world applicability of geothermal machine learning projects.

access↗
DOE OSTI2022

Assessment of Economic Impact of Permitting Timelines on Produced Geothermal Power in Imperial County, California

Despite having a large geothermal power potential in the United States, only a small fraction has been developed for power generation. Various barriers, including technical, financial, and regulatory permit delays, are attributed to lower contribution of geothermal energy in the national grid. Unpredictable environmental reviews and permitting timelines are some of the non-technical barriers that can cause delays in geothermal exploration and utilization plans. Our study shows that the geothermal permitting timelines can vary from six months to several years, depending on the presence or absence of biological resources, cultural resources, and sensitive environmental issues at the project site. The potential impacts of these permit barriers can range from investors abandoning geothermal development to making the product (i.e., electricity) more expensive and uncompetitive. In this study, we conducted economic analysis to assess the impact of permitting timelines on cost of produced electricity from geothermal resources using data from existing geothermal plants as well as prospective sites. In this paper, we present collected timelines data, approach, and results of economic impact of permitting timelines on geothermal power. We evaluated the various environmental management and permit review processes by considering a hypothetical geothermal project in the Salton Sea Known Geothermal Resource Area. Because of the variety of the biological and environmental issues and the involvement of local, state, and federal agencies with overlapping jurisdictions, this project could go through one of the many California Environmental Quality Act (CEQA) and National Environmental Policy Act (NEPA) review scenarios that range from the least to the most complex in its circumstances. The fastest CEQA/NEPA review timelines would have the project completed in six years. In contrast, the project would substantially need longer time to complete if it were located in an area with significant environmental resources or cultural issues that required permitting from various agencies. With increasing project completion timelines, the simplified levelized cost of electricity (sLCOE) can be 4 to 11% higher with longer CEQA/NEPA review timelines than the sLCOE value with the fastest CEQA/NEPA review timeline. Lengthier CEQA/NEPA review timelines could also result in loss of $64 million to $227 million in potential revenue. Such significant economic impacts could determine the success of a geothermal project.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Energy Transitions Initiative Partnership Project: ETIPP Technical Assistance Informational Webinar

This webinar is for prospective applicants (i.e., remote, island, and islanded communities) interested in applying to the U.S. Department of Energy's Energy Transitions Initiative Partnership Program (ETIPP) in spring of 2022. This webinar provides an overview of ETIPP and technical assistance, introduces the ETIPP regional partners, summarizes two ongoing ETIPP projects, discusses the 2022 application process, and closes with a question-and-answer session. This webinar is hosted by the National Renewable Energy Laboratory, which is part of the ETIPP partner network.

Alaska Center for Energy and Power↗
DOE OSTI2022

DIS physics at the EIC and LHeC and connections to the future LHC and $\nu$A programs

Deeply-inelastic scattering (DIS) stands to enter a golden age with the prospect of precision programs at the Electron-Ion Collider (EIC) and Large Hadron-electron Collider (LHeC). While these programs will be of considerable importance to resolving longstanding issues in (non)perturbative QCD as well as hadronic and nuclear structure, they will also have valuable implications for a wider range of physics at the Energy and Intensity Frontiers, including at the High-Luminosity LHC (HL-LHC) and future $\nu A$ facilities. In this plenary contribution, we highlight a number of salient examples of the potential HEP impact from the complementary EIC and LHeC programs drawn from their respective Yellow Report and Whitepaper. Interested readers are encouraged to consult the extensive studies and literature from which these examples are taken for more detail.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Snowmass2021 Cosmic Frontier Dark Matter Direct Detection to the Neutrino Fog

We present a summary of future prospects for direct detection of dark matter within the GeV/c2 to TeV/c2 mass range. This is paired with a new definition of the neutrino fog in order to better quantify the rate of diminishing returns on sensitivity due to irreducible neutrino backgrounds. A survey of dark matter candidates predicted to fall within this mass range demonstrates that fully testing multiple well-motivated theo-ries will require expanding the currently-funded generation of experiments down to and past the neutrino fog. We end with the status and plans for next-generation exper-iments and novel R&D concepts which will get us there.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Quantum computing hardware for HEP algorithms and sensing

Quantum information science harnesses the principles of quantum mechanics to realize computational algorithms with complexities vastly intractable by current computer platforms. Typical applications range from quantum chemistry to optimization problems and also include simulations for high energy physics. The recent maturing of quantum hardware has triggered preliminary explorations by several institutions (including Fermilab) of quantum hardware capable of demonstrating quantum advantage in multiple domains, from quantum computing to communications, to sensing. The Superconducting Quantum Materials and Systems (SQMS) Center, led by Fermilab, is dedicated to providing breakthroughs in quantum computing and sensing, mediating quantum engineering and HEP based material science. The main goal of the Center is to deploy quantum systems with superior performance tailored to the algorithms used in high energy physics. In this Snowmass paper, we discuss the two most promising superconducting quantum architectures for HEP algorithms, i.e. three-level systems (qutrits) supported by transmon devices coupled to planar devices and multi-level systems (qudits with arbitrary N energy levels) supported by superconducting 3D cavities. For each architecture, we demonstrate exemplary HEP algorithms and identify the current challenges, ongoing work and future opportunities. Furthermore, we discuss the prospects and complexities of interconnecting the different architectures and individual computational nodes. Finally, we review several different strategies of error protection and correction and discuss their potential to improve the performance of the two architectures. This whitepaper seeks to reach out to the HEP community and drive progress in both HEP research and QIS hardware.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Advancing Superconducting Magnet Diagnostics for Future Colliders

Future colliders will operate at increasingly high magnetic fields pushing limits of electromagnetic and mechanical stress on the conductor [1]. Understanding factors affecting superconducting (SC) magnet performance in challenging conditions of high mechanical stress and cryogenic temperatures is only possible with the use of advanced magnet diagnostics. Diagnostics provide a unique observation window into mechanical and electromagnetic processes associated with magnet operation, and give essential feedback to magnet design, simulations and material research activities. Development of novel diagnostic capabilities is therefore an integral part of next-generation magnet development. In this paper, we summarize diagnostics development needs from a prospective of the US Magnet Development Program (MDP), and define main research directions that could shape this field in the near future.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Dual-Readout Calorimetry for Future Experiments Probing Fundamental Physics

In this White Paper for the 2021 Snowmass process, we detail the status and prospects for dual-readout calorimetry. While all calorimeters allow estimation of energy depositions in their active material, dual-readout calorimeters aim to provide additional information on the light produced in the sensitive media via, for example, wavelength and polarization, and/or a precision timing measurements, allowing an estimation of the shower-by-shower particle content. Utilizing this knowledge of the shower particle content may allow unprecedented energy resolution for hadronic particles and jets and new types of particle flow algorithms. We also discuss the impact continued development of this kind of calorimetry could have on precision on Higgs boson property measurements at future colliders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Integration and Packaging

Vertically integrated (3D) combinations of sensors and electronics provide the ability to fabricate small, fine pitch pixels with very small total capacitance monolithically integrated with complex circuitry. The small capacitance, enabled by the fine pixel pitch and low interconnect capacitance available in 3D hybrid bonding, provides excellent signal/noise with moderate power. This combination enables fabrication of integrated sensors and electronics with both excellent position and time resolution. In this white paper a discussion will be presented on 3D integration advantages, ongoing projects and prospects in high energy physics and beyond.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗