Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “resource consumption”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Can Food–Energy–Water Nexus Research Keep Pace with Agricultural Innovation?

The interconnection among food–energy–water (FEW) systems in meeting societal demands is broadly acknowledged. Similarly, competitive or synergistic allocations of water and energy resources for agricultural production, manufacturing, and human consumption are understood, and their economic impacts can be predicted. Far less appreciated and understood are the outcomes of the FEW nexus in response to operation changes in agricultural practices and the associated technological innovations for future generations. Also, the inter-scale and feedback effects of emerging technology-driven resource reallocation and decision-making on FEW systems are largely unknown. For example, how do the agroeconomic feedbacks of intelligent technologies influence the FEW nexus of agricultural production under environmental and demographic changes? How does the necessary water allocation for powering non-powered dams and pumped-storage hydropower generation influence agricultural production and municipal water supply maintenance? How do solar and wind energy farms influence land use for agriculture and the rural economy? In turn, how can the generated solar and wind energy help reduce the cost of groundwater extraction or water desalination?

42 ENGINEERING↗
DOE OSTI2022

Vertebrate and invertebrate competition for carrion in human‐impacted environments depends on abiotic factors

Abstract Human altered landscapes have caused declines in the diversity of wildlife where behaviorally plastic species (i.e., mesocarnivores and invasive species) tend to monopolize these areas and consume predictable and readily accessible food resources, such as human food waste and carrion. Increased consumption of carrion by vertebrates and invasive invertebrate species can alter population dynamics of native necrophagous insects relying on these resources. We tested the hypothesis that vertebrate scavengers and invasive species reduce blow fly (1) ability to use carrion and (2) reproduction in human‐impacted environments in central Texas, USA, with season, habitat (field and wooded landscapes), and carrion type (species of carrion and coat color) acting synergistically. Vertebrate scavengers in this habitat, of which 75% of the documented species were mesocarnivores and obligate scavengers, consumed 100% of carrion during the winter and 62% during summer despite having low species richness (2–5 species). Of the remaining carcasses available for arthropod activity during summer, the invasive red imported fire ant, Solenopsis invicta (Hymenoptera: Formicidae), monopolized 34%, and blow flies (e.g., Lucilia eximia and Chrysomya rufifacies [Diptera: Calliphoridae]) were only able to colonize 25%. Approximately 90% of carrion that was utilized by blow flies was co‐colonized by fire ants, and subsequent production of adult blow flies experienced up to a ninefold reduction in production compared with carcasses that were not scavenged by vertebrates or fire ants. Our results demonstrate oviposition resources used by blow flies in environments altered by human activity are reduced significantly by vertebrate scavengers and an invasive ant species. Future research should determine whether competitive interactions between vertebrate and invasive ant competitors for access to carrion resources have population‐level impacts to blow flies in human‐mediated ecosystems, or whether blow flies are able to shift to other resources to maintain sustainable populations and continue providing ecosystem services, such as pollination.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Creating a Research Enterprise Framework for Transdisciplinary Networking to Address the Food–Energy–Water Nexus

Urbanization, population growth, and the accelerating consumption of food, energy, and water (FEW) resources bring unprecedented challenges for economic, environmental, and social (EES) sustainability. It is imperative to understand the potential impacts of FEW systems on the realization of the United Nation’s Sustainable Development Goals (SDGs) as the world transitions from natural ecosystems to managed ecosystems at an accelerating rate. A major obstacle is the complexity and emergent behavior of FEW systems and associated networks, for which no single discipline can generate a holistic understanding or meaningful projections. We propose a research enterprise framework for promoting transdisciplinarity and top-down quantification of the interrelationships between FEW and EES systems. Relevant enterprise efforts would emphasize increasing FEW resource accessibility by improving coordinated interplays across sectors and scales, expanding and diversifying supply-chain networks, and innovating technologies for efficient resource utilization. This framework can guide the development of strategic solutions for diminishing the competition among FEW-consuming sectors in a region or country, and for minimizing existing inequalities in FEW availability when a sustainable development agenda is implemented.

42 ENGINEERING↗
DOE OSTI2020

Sharpening Nanofiltration: Strategies for Enhanced Membrane Selectivity

Nanofiltration plays an increasingly large role in many industrial applications, such as water treatment (e.g., desalination, water softening, and fluoride removal) and resource recovery (e.g., alkaline earth metals). Energy consumption and benefits of nanofiltration processes are directly determined by the selectivity of the nanofiltration membranes, which is largely governed by pore-size distribution and Donnan effects. During operation, the separation performance of unmodified nanofiltration membranes will also be impacted (deleteriously) upon unavoidable membrane fouling. Many efforts, therefore, have been directed toward enhancing the selectivity of nanofiltration membranes, which can be classified into membrane fabrication method improvement and process intensification. Finally, this review summarizes recent developments in the field and provides guidance for potential future approaches to improve the selectivity of nanofiltration membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

A mission to Mercury and a mission to the moons of Mars

Two Advanced Design Projects were completed this academic year at Penn State - a mission to the planet Mercury and a mission to the moons of Mars (Phobos and Deimos). At the beginning of the fall semester the students were organized into six groups and given their choice of missions. Once a mission was chosen, the students developed conceptual designs. These designs were then evaluated at the end of the fall semester and combined into two separate mission scenarios. To facilitate the work required for each mission, the class was reorganized in the spring semester by combining groups to form two mission teams. An integration team consisting of two members from each group was formed for each mission team so that communication and exchange of information would be easier among the groups. The types of projects designed by the students evolved from numerous discussions with Penn State faculty and mission planners at the Lewis Research Center Advanced Projects Office. Robotic planetary missions throughout the solar system can be considered valuable precursors to human visits and test beds for innovative technology. For example, by studying the composition of the Martian moons, scientists may be able to determine if their resources may be used or synthesized for consumption during a first human visit.

Source record↗
NASA NTRS2022

Mission Planning for Trident: Discovery proposal to Neptune’s moon, Triton

Trident was one of the four Discovery-class Step-1 mission proposals selected by NASA in 2020 for further development and study; however, in 2021, the Step-2 proposal was not down-selected to transition into the next phase of mission development, i.e., a mission for flight.Neptune’s largest moon, Triton, was the primary focus of study for Trident. Triton’s physical and orbital characteristics make it a unique planetary target for scientific exploration, providing opportunities for investigations in a wide variety of scientific fields, including geomorphological, atmospheric, geophysical, magnetospheric, and ionospheric studies. The science objectives of the Trident mission encompassed an in-depth interior-to-exterior set of objectives, focused on multiple outstanding questions resulting from the 1989 encounter of Voyager 2, and subsequent analysis.Ball Aerospace Corp. was tasked with building the Trident spacecraft, with JPL responsible for providing Engineering Support (Mission Design & Navigation, Mission Planning, Flight Operations, Ground Data Systems, Systems Engineering) and leading Project Management. The observatory would carry a wide-ranging suite of scientific instruments onboard, including an Infrared Spectrometer (IRS) and Narrow Angle Camera (NAC) to be provided by Ball Aerospace Corp., a Wide Angle Camera (WAC) from JPL, a Magnetometer from UCLA, a contributed Plasma Science Suite from IRF (Sweden), and a contributed Radio Science instrument from ASI (Italy). All of these instruments would be used to collect unique datasets during the Triton encounter. Trident would have taken advantage of an ~13-yr, nearly-ballistic trajectory to Triton, utilizing a timely Jupiter Gravity Assist, to execute a 10-day long encounter in the Neptunian system. Launch was planned for October 2025, with Triton arrival scheduled for December 2038. The timeline for this mission would have been sub-divided into seven major phases: Launch, Commissioning, Inner Planet Cruise, Outer Planet Cruise, Approach, Encounter, and Science Data Return. Multiple planetary flybys were planned to be performed during the cruise, including three Earth flybys and one Venus flyby in the Inner Planet Cruise phase, and one Jupiter flyby in the Outer Planet Cruise phase. Along with conventional (Range and Doppler) tracking data, Delta-DOR and Optical Navigation data were also to be acquired to assist with spacecraft navigation during the Approach and Encounter phases. A 3 meter X-Band High Gain Antenna would allow playback of all science data at 1 kbps within 1 year after the Triton Encounter. The Mission Planning element on Trident encompassed and informed multiple aspects of this proposal, ranging from science observation planning during the Triton Encounter phase, to generation of activity timelines for all mission phases; performing ground coverage analysis for science observations to be acquired by all instruments and tracing them to science requirements; evaluation of spacecraft resources including data volume stored onboard, power/energy consumption, telecom (commanding/telemetry) requirements, and overall, working at the interface of science and engineering teams on the mission. All of these functions that were performed by the Mission Planning team on this proposal are discussed in this paper.

Prockter, Louise↗
DOE OSTI2021

Systems and methods for randomized, packet-based power management of conditionally-controlled loads and bi-directional distributed energy storage systems

The present disclosure provides a distributed and anonymous approach to demand response of an electricity system. The approach conceptualizes energy consumption and production of distributed-energy resources (DERs) via discrete energy packets that are coordinated by a cyber computing entity that grants or denies energy packet requests from the DERs. The approach leverages a condition of a DER, which is particularly useful for (1) thermostatically-controlled loads, (2) non-thermostatic conditionally-controlled loads, and (3) bi-directional distributed energy storage systems. In a first aspect of the present approach, each DER independently requests the authority to switch on for a fixed amount of time (i.e., packet duration). The coordinator determines whether to grant or deny each request based electric grid and/or energy or power market conditions. In a second aspect, bi-directional DERs, such as distributed-energy storage systems (DESSs) are further able to request to supply energy to the grid.

Frolik, Jeff↗
DOE OSTI2022

Controlled-Environment Agriculture and the Geography of Food, Energy and Water Resilience in the United States

USDA guidelines call for an increase in fruit and vegetable consumption in U.S. households to promote healthier diets. Access to fresh fruits and vegetables are especially lacking in food deserts and food swamps (characterized by a prevalence of food that is highly processed and lacking in nutritional value). Adoption of the recommended healthy diet, which more than doubles the consumption of fruits and vegetables, would have a wide variety of health benefits and would reduce the land footprint of U.S diets. However, adopting a healthy diet would increase phosphate and nitrogen impacts associated with fertilizers and pesticides and would significantly increase freshwater consumption and energy use because of the resource intensity of field cultivation of fruits and vegetables. The majority of these crops are grown in just a few states, including California and Arizona, which are increasingly impacted by climate change. In addition, rural communities are rapidly becoming food deserts, while food produced in these areas is transported long distances to market. In recent years, highly intensified controlled environment (CE) agricultural systems, (i.e., vertical farming) have been developed to provide fresh food closer to consumers. Fruits and vegetables, many of which are amenable to CE culture, occupy a uniquely impactful segment of the food supply-chain, including their value in improving nutrition for vulnerable communities. The objective of this work is to elucidate the location dependency of the energy and water impacts of adoption of distributed CE farming for an important portion of the food system.

controlled environment agriculture↗
DOE OSTI2024

Systems and methods for randomized energy draw or supply requests

The present disclosure can provide a distributed and anonymous approach to demand response of an electricity system. The approach can conceptualize energy consumption and production of distributed-energy resources (DERs) via discrete energy packets that are coordinated by a cyber computing entity that grants or denies energy packet requests from the DERs. The approach leverages a condition of a DER, which is particularly useful for (1) thermostatically-controlled loads, (2) non-thermostatic conditionally-controlled loads, and (3) bi-directional distributed energy storage systems, among others. In a first aspect of the present approach, each DER independently requests the authority to switch on for a fixed amount of time (i.e., packet duration). The coordinator determines whether to grant or deny each request based electric grid and/or energy or power market conditions. In a second aspect, bi-directional DERs, such as distributed-energy storage systems (DESSs) are further able to request to supply energy to the grid.

Frolik, Jeff↗
NASA NTRS2000

Calculating space station resource prices

This paper describes how we calculate ISS resource shadow prices from the first-order cost minimization conditions using MESSOC and engineering cross-consumption models.

International↗
DOE OSTI2025

Designing reinforcement learning algorithms for building HVAC control: From experimental observation to simulation comparisons

Advanced supervisory-level control with reinforcement learning (RL) is regarded as a promising solution for HVAC systems to minimize energy consumption while maintaining thermal comfort and indoor air quality. However, most RL applications were conducted in the simulation environment rather than real-world HVAC systems. This paper developed a value-based RL controller termed Deep Q-Network (DQN) for a typical central HVAC system and evaluated its performance in a building test facility. By comparing DQN with a rule-based controller, the study not only demonstrated the cases where DQN could properly maintain indoor comfort but also discussed possible reasons why DQN failed in some other situations. Recognizing the limitations of value-based RL algorithms from the experimental tests, a simulation study was conducted to compare DQN with an alternative RL approach, an actor–critic algorithm termed Deep Deterministic Policy Gradient (DDPG). In scenarios with a relatively large action space, DDPG outperformed DQN by requiring fewer computational resources and achieving better thermal comfort, lower energy consumption, and more stable control actions. The findings suggest that the ability of DDPG to handle continuous control variables more effectively allows for faster convergence in training and more precise control in practice, which enhances the overall efficiency and reliability of the HVAC system.

Guo, Fangzhou↗
DOE OSTI2024

Optimizing and Exploring Untapped Micro-Hydro Hybrid Systems: a Multi-Objective Approach for Crystal Lake as a Large-Scale Energy Storage Solution

Increasing electricity demand and concerns about climate change and fossil fuel consumption have highlighted the importance of renewable energy resources and storage systems. This paper proposes a method for exploring untapped pumped hydro storage potentials to accommodate intermittent renewable energy generation profiles. Hourly measured data from 2022 in Benzie County, Michigan, United States, were gathered for system sizing and a thorough, realistic analysis. By employing the multi-objective grey wolf optimization algorithm, we formulated optimal sizing and energy-management strategies for three different scenarios. Unlike similar studies, the 3rd with triple objective functions (OFs) scenario aims to maximize both reliability and ecological OFs while minimizing the cost OF. It has shown promising results with multiple solutions, considering economic, environmental, and reliability factors. A case study conducted in Crystal Lake, Michigan, revealed that although Crystal Lake would function only as a micro-hydro power facility, it is a promising and huge storage unit with a substantial storage capacity of around 14.9734GWh. The system investigated is significant in the USA due to its rapid deployment capabilities, minimal construction requirements, and ease of integration with the distribution grid. The fuzzy logic method was employed to identify the best non-dominant solution among the other solutions. Furthermore, these outcomes include a notably low levelized cost of energy at 0.046147$/kWh, a robust index of reliability of 99.705%, and a significant reduction in CO₂ emissions amounting to 7.9142×10 3 tons/year, when considering the triple OFs. The paper’s methodology provides valuable insights for regions aiming to utilize renewable energy from untapped storage sources.

13 HYDRO ENERGY↗
DOE OSTI2022

Enhanced deep neural networks with transfer learning for distribution LMP considering load and PV uncertainties

As the flexibility of generation and demand increases in distribution systems, the residential loads are emerging as a promising means to participate in demand response and the transactive energy market. Market pricing is an instrumental mechanism for the distribution system operator to exploit the full potential of the flexible resources. The distribution locational marginal price (DLMP) can be used to guide the residential load consumption. This type of market signal helps the distribution system operator to optimize the scheduling of all resources while satisfying related network constraints through a day-ahead market. However, solving the optimization problem for large-scale systems can be computationally expensive. To address the scalability and practicability limitations of the DLMP framework, a learning-based approach is proposed in this paper to complement the day-ahead distribution market framework. Here, the proposed approach combines long short-term memory and transfer learning to develop deep neural network that can capture the spatial–temporal correlation of the input data. The model can determine the optimal DLMP for each node in a distribution system without the system parameters required to formulate the optimization problem. Testing results on IEEE 33-bus and 123-bus systems show that the proposed approach can generate a comparable DLMP against the optimization solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Combining Agent Based Modeling and System Dynamics to Investigate the Circularity of Plastics

The United States currently produces about 1 million metric ton of ocean plastic pollution annually. One proposed solution to combat plastic waste is a circular economy (CE), which aims to transition from today's take-make-waste linear pattern of production and consumption to a system where the value of resources is maximized over time. Two key methods in industrial ecology are useful in assessing the viability of CE: (1) System Dynamics (SD) and (2) Agent Based Modeling (ABM). In prior work, the plastic life cycle was modeled with SD and ABM. The two models calculate recycling rates and costs in different ways, making it difficult to pinpoint necessary next steps. We integrate the ABM and SD models - linking the emergent patterns from micro-level human decisions to system level processes - which allows a more comprehensive understanding of feedbacks, costs, and environmental impacts. The integrated model is more accurate, and can be used to visualize recycling rates and human health and environmental impacts over time. The difference between the integrated and original SD model prompts a Sobol sensitivity analysis, which is used to understand which behavioral factors most affect plastic recycling patterns. We find that the habitual component is typically the most influential in promoting positive recycling behavior. Additionally, we utilize the combined model to understand and visualize how various behavioral intervention scenarios, like improved access to recycling programs and cart tagging, influence recycling patterns; these results can guide future policy-making.

agent-based modeling↗
DOE OSTI2022

Golden Gate National Recreation Area Federal Fleet Tiger Team EVSE Site Assessment

The U.S. Department of Energy Federal Energy Management Program (FEMP) helps federal agencies reduce petroleum consumption and increase alternative fuel use through its resources for sustainable federal fleets. A key element of this assistance involves supporting agencies in the transition to zero-emission vehicles (ZEVs). Fleet electrification is part of a federal policy to achieve net-zero emissions economy-wide and a carbon pollution-free electricity sector, established through two executive orders (EOs) - EO 14008: Tackling the Climate Crisis at Home and Abroad and EO 14057: Catalyzing America's Clean Energy Industries and Jobs through Federal Sustainability. This site report supports the development of a ZEV deployment plan for the Golden Gate National Recreation Area, which can ultimately be incorporated into the overall U.S. Department of the Interior ZEV fleet strategy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Grand Teton National Park Federal Fleet Tiger Team EVSE Site Assessment

The U.S. Department of Energy Federal Energy Management Program (FEMP) helps federal agencies reduce petroleum consumption and increase alternative fuel use through its resources for sustainable federal fleets. A key element of this assistance involves supporting agencies in the transition to zero-emission vehicles (ZEVs). Fleet electrification is part of a federal policy to achieve net-zero emissions economy-wide and a carbon pollution-free electricity sector, established through two executive orders (EOs) - EO 14008: Tackling the Climate Crisis at Home and Abroad and EO 14057: Catalyzing America's Clean Energy Industries and Jobs through Federal Sustainability. This site report supports the development of a ZEV deployment plan for the Grand Teton National Park (GRTE) that can ultimately be incorporated into the overall Department of the Interior ZEV fleet strategy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Yellowstone National Park Federal Fleet Tiger Team EVSE Site Assessment [Slides]

The U.S. Department of Energy Federal Energy Management Program (FEMP) helps federal agencies reduce petroleum consumption and increase alternative fuel use through its resources for sustainable federal fleets. A key element of this assistance involves supporting agencies in the transition to zero-emission vehicles (ZEVs). Fleet electrification is part of a federal policy to achieve net-zero emissions economy-wide and a carbon pollution-free electricity sector, established through two executive orders (EOs) - EO 14008: Tackling the Climate Crisis at Home and Abroad and EO 14057: Catalyzing America's Clean Energy Industries and Jobs through Federal Sustainability. This site report supports the development of a ZEV deployment plan for Yellowstone National Park, which can ultimately be incorporated into the overall U.S. Department of the Interior ZEV fleet strategy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Multi-scale Simulation, Calibration, and Optimization of Calcium Carbonate Precipitation in Microbial Communities

Ensuring the efficient engineering of microbially induced calcium carbonate precipitation (MICP) is crucial for a variety of environmental and civil engineering applications, such as soil stabilization and carbon sequestration. Addressing this need, we present a comprehensive multi-scale workflow that begins with the isolation of calcium carbonate-producing microbes from soil samples, followed by metagenomic sequencing and metabolic reconstruction. We then characterize microbial growth phenotypes under diverse nutrient conditions, compare observed growth with metabolic model predictions, and apply the Consistent Reproduction of Phenotype (CROP) algorithm to refine these models. Furthermore, we analyze metabolite consumption and production, and develop a consumer-resource model that is calibrated using time-series measurements of growth rates, pH levels, and calcium carbonate precipitation. The primary benefit of our approach lies in its ability to predict and control MICP outcomes, facilitated by a Bayesian methodology that incorporates priors on initial conditions and parameters. This allows us to compute posteriors by integrating experimental data, and to solve a risk optimization problem under uncertainty to identify nutrient conditions that maximize calcium carbonate production. In contrast to non-Bayesian methods, which fail to quantify uncertainty accurately, our approach provides a more reliable pathway to optimizing nutrient conditions, enhancing the likelihood of achieving desired MICP outcomes. This positions our method as a superior alternative in the quest to improve MICP through engineered microbial consortia.

54 ENVIRONMENTAL SCIENCES↗