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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Role of Fuels in Transforming Energy End-Use in Buildings and Industrial Processes

This book examines what role fuels have in the transformation of end-use in buildings and industrial processes. Energy efficient technologies are necessary to lower the carbon footprint for a transition towards clean energy in a sustainable manner. Efficient utilization of primary energy resources including renewables to support the current and future energy needs while targeting grid resiliency, energy and environmental security, at an affordable cost is of significant value. Analysis of configurations consisting of heat pumps, fuel driven thermal providers and power systems is presented. Sensitivity of electrical grid's carbon intensity towards carbon footprint in comparison with fuel driven technologies is necessary to recognize the true value proposition of currently available energy solutions for different end consumers. Similarly, the role of low carbon, zero carbon, and carbon negative fuels such as power to gas, power to liquid, hydrogen, biogas, etc. in conjunction with polygeneration technologies are discussed. Transformation of the primary energy resources from conventional fossil fuels to renewable fuels or electricity will have a significant impact on the overall carbon footprint of various end use sectors, including buildings. Hence, this book also examines two different scenarios focused on sensitivity of the pace of decarbonization of electrical grid and fuel supply on operational energy related carbon emissions.

Cheekatamarla, Praveen↗
DOE OSTI2022

A machine learning approach for clinker quality prediction and nonlinear model predictive control design for a rotary cement kiln

Abstract Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard “Bogue’ model”. The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges.

Ali, Asem M.↗
DOE OSTI2024

Sustainable Aviation Fuel Combustion, Soot, and Contrail Formation

The aviation industry stands at a crossroads, facing the dual challenge of meeting the growing global demand for air travel while mitigating its environmental impact. As concerns over climate change intensify, sustainable aviation fuels (SAFs) have emerged as a promising solution to reduce the carbon footprint of air travel. The aviation sector has long been recognized as a contributor to greenhouse gas emissions, with carbon dioxide (CO 2 ) being a primary concern. SAFs, derived from renewable feedstocks such as biomass, waste oils, or synthetic processes, offer a promising avenue for reducing the net carbon emissions associated with aviation. While SAFs have shown potential in lowering CO 2 emissions, the combustion process introduces complexities related to soot particle formation and contrail generation that require comprehensive exploration. These aspects are pivotal not only for their environmental implications but also for their influence on atmospheric climate interactions. As the aviation industry increasingly embraces SAFs to meet sustainability goals, it is imperative to assess their combustion characteristics, unravel the mechanisms of soot formation, and scrutinize the factors influencing contrail development.

09 BIOMASS FUELS↗
DOE OSTI2025

Life-Cycle Emissions and Human Health Implications of Multi-Input, Multi-Output Biorefineries

To meaningfully broaden the supply of fuels for the transportation sector, biofuel production must be scaled up and this requires a wider array of biomass feedstocks, including agricultural residues and organic waste. Rather than pursuing conversion of lignocellulosic biomass to fuels and anaerobic digestion of wastes as separate pathways, there are economic and environmental advantages associated with integrating these processes in a single facility. However, existing research rarely goes beyond carbon footprints in quantifying the effects of such a shift in bioenergy production. In addition to CO2, CH4, and N2O, this study explores the life-cycle air pollution (NH3, volatile organic compounds, NOx, SO2, and PM2.5), marine eutrophication, acidification, and local external cost implications of biorefineries capable of taking in crop residues, food waste, and manure to produce liquid fuel, electricity, and/or other options such as renewable natural gas (RNG), hydrogen, bioplastics, and protein-rich livestock feed. Relative to a single-input, single-output baseline, biorefineries integrated with organic waste codigestion to coproduce electricity or RNG can reduce life-cycle CO2-equivalent emissions by 84-149%, and the monetized external impacts across all scenarios range from $1.07/gallon to -$0.75/gallon ethanol.

Air pollution↗
DOE OSTI2024

Estimating the carbon footprint of computational fluid dynamics

In this study, computational resources have grown exponentially in the past few decades. These machines make possible research and design in fields as diverse as medicine, astronomy, and engineering. Despite ever-increasing computational capabilities, direct simulation of complex systems has remained challenging owing to the degrees of freedom involved. At the cusp of exascale computing, high-resolution simulation of practical problems with minimal model assumptions may soon experience a renaissance. However, growing reliance on modern computers comes at the cost of a growing carbon footprint. To illustrate this, we examine historic computations in fluid dynamics where larger computers have afforded the opportunity to simulate flows at increasingly relevant Reynolds numbers. Under a variety of flow configurations, the carbon footprint of such simulations is found to scale roughly with the fourth power of Reynolds number. This is primarily explained by the computation cost in core-hours, which is also described by similar scaling, though regional differences in renewable energy use also play a role. Using the established correlation, we examine a large database of simulations to develop estimates for the carbon footprint of computational fluid dynamics in a given year. Collectively, the analysis provides an additional benchmark for new computations where, in addition to balancing considerations of model fidelity, carbon footprint should also be considered.

42 ENGINEERING↗
NASA NTRS2014

Detecting Change in Urban Areas at Continental Scales with MODIS Data

Urbanization is one of the most important components of global environmental change, yet most of what we know about urban areas is at the local scale. Remote sensing of urban expansion across large areas provides information on the spatial and temporal patterns of growth that are essential for understanding differences in socioeconomic and political factors that spur different forms of development, as well the social, environmental, and climatic impacts that result. However, mapping urban expansion globally is challenging: urban areas have a small footprint compared to other land cover types, their features are small, they are heterogeneous in both material composition and configuration, and the form and rates of new development are often highly variable across locations. Here we demonstrate a methodology for monitoring urban land expansion at continental to global scales using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The new method focuses on resolving the spectral and temporal ambiguities between urban/non-urban land and stable/changed areas by: (1) spatially constraining the study extent to known locations of urban land; (2) integrating multitemporal data from multiple satellite data sources to classify c. 2010 urban extent; and (3) mapping newly built areas (2000-2010) within the 2010 urban land extent using a multi-temporal composite change detection approach based on MODIS 250 m annual maximum enhanced vegetation index (EVI). We test the method in 15 countries in East-Southeast Asia experiencing different rates and manifestations of urban expansion. A two-tiered accuracy assessment shows that the approach characterizes urban change across a variety of socioeconomic/political and ecological/climatic conditions with good accuracy (70-91% overall accuracy by country, 69-89% by biome). The 250 m EVI data not only improve the classification results, but are capable of distinguishing between change and no-change areas in urban areas. Over 80% of the error in the change detection can be related to definitional issues or error propagation, rather than algorithm error. As such, these methods hold great potential for routine monitoring of urban change, as well as for providing a consistent and up-to-date dataset on urban extent and expansion for a rapidly evolving region.

Urban areas↗
DOE OSTI2023

Evaluating the carbon footprint of the integrated DBD‐plasma bi‐reforming unit via laboratory scale experiments and scaled‐up process modeling

Catalytic dielectric barrier discharge (DBD) plasma reactor experiments were performed in a tubular glass reactor with a 2 mm gap at 550°C to facilitate the reaction kinetics of steam added dry reforming or bireforming. The best specific energy input obtained was 11.2 eV/molecule feed at CO 2 :CH 4 :H 2 O of 4.5:1:4.5 ratio and gas hour space velocity (GHSV) = 432 h −1 . This value was used to design a conceptual process and assess the environmental impact of methane steam reforming-based H 2 production 18.4 kmol/h CO 2 emission processing into H 2 :CO = 2 syngas, with an emphasis on the carbon footprint.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Comprehensive process and environmental impact analysis of integrated DBD plasma steam methane reforming

Utilization of electricity generated from renewable sources to obtain hydrogen, H 2 , is of critical importance to decrease the overall carbon footprint. Here in this work, integration of a dielectric discharge barrier (DBD) plasma reactor to convert low calorific value gas, such as landfill gas or coal mine gas into hydrogen, into the existing steam methane reforming (SMR) technology was evaluated using process design considerations. In particular, a DBD-enhanced catalytic SMR reactor was modeled to operate at near atmospheric pressure and 500 °C sequentially with the conventional reformer to obtain ~ 65 kmol/hr H2 for distributed production. This allowed decreasing the size of the conventional reformer albeit at the increased overall electricity consumption. Calculated process economics showed that only at an electricity cost of less than $0.004/kWh does the hybrid DBD plasma process derived H 2 price become competitive with that of the conventional SMR. A Life Cycle Assessment framework was used to compare environmental impacts from the conventional SMR, hybrid DBD SMR and hybrid DBD SMR utilizing only onshore wind-derived electricity. Larger environmental impacts in the plasma reformer were obtained due to the use of electricity for the plasma reforming operation, which was modeled as coming from the typical U.S. grid mix. Utilizing only 100% wind-derived electricity provided certain environmental benefits, except for the ecotoxicity impact where the wind power scenario modeled here only reduced ecotoxicity impacts associated with electricity by 30%.

08 HYDROGEN↗
DOE OSTI2023

Quantifying the environmental benefits of a solvent-based separation process for multilayer plastic films

Food packaging often appears in the form of multilayer (ML) plastic films, which leverage the functional properties of different polymers to achieve specific food protection goals (e.g., oxygen, water, and temperature barriers). These properties are essential to enable long shelf lives, reduce refrigeration usage, mitigate food waste, and increase food accessibility. However, ML film production processes generate large amounts of plastic waste that cannot be mechanically recycled. Recently, we have proposed a process, called solvent-targeted recovery and precipitation (STRAP), that enables the separation and recycling of the constituent polymers of ML films. This technology uses a series of solvent washes that selectively dissolve and precipitate target polymers. Quantifying the environmental benefits of STRAP over virgin resin production is essential for the commercial deployment of this technology. Further, this work uses life cycle assessment (LCA) methods to evaluate these impacts in terms of carbon footprint, energy use, water use, and toxicity. We analyze three STRAP process variants that use antisolvent and temperature-driven precipitation to treat different ML films. Our analysis reveals that the STRAP-A and STRAP-B process variants can provide environmental benefits over virgin film production. Furthermore, it gives valuable insight into the critical components of ML films (specific polymers) and of the STRAP processes (equipment) that are responsible for the highest impacts. Ultimately, we believe that the proposed analysis framework can lead to the design of more environmentally-friendly ML films and recycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Economic and environmental impacts of a non-traditional combined heat and power system for a discrete manufacturing facility

Combined heat and power (CHP) is an electricity generation strategy that benefits all sides with a vested interest in the nations’ energy future. The technology allows for the efficient production of electricity and heat, which in turn reduces the carbon footprint and energy costs of a facility with significant heat and electricity loads. This paper investigates, through a detailed dynamic simulation, how a highly non-traditional CHP facility can leverage those forces to economically and environmentally benefit. Four system configurations of a composites manufacturing facility, one existing and three proposed systems, including two CHP configurations and one combined cooling, heating, and power (CCHP) configuration are evaluated from both economic and environmental views. The three proposed configurations are based on a 600 kW microturbine as the primary mover. The dynamic model showed great potential to capture the dynamics of the system configurations including the dynamics of temperature, oven exhaust fraction, electrical efficiency, and overall efficiency of the system configurations. All 3 CHP systems have a payback period between 8.03 and 8.33 years. The proposed system configurations reduce up to 22.7% of the CO 2 emission compared to the existing facility, supplying the demands in a cleaner manner.

42 ENGINEERING↗
NASA NTRS2016

On-Orbit Manufacturing From Orbital Factories to In Situ Resource Utilization

This webinar will review commercial prospects for manufacturing in orbit. Doing business in space is rapidly becoming more reliable, affordable and accessible. From 2010 to 2015 launch prices went down by a factor of 10 or more, to about $5,000kg while investments into Space 2.0 companies and technologies are closing in on $2.5 Billion (New Space Global). With three commercial suppliers (SpaceX, Orbital ATK and Sierra Nevada Corp) to Earths orbits, mission frequency is improving dramatically. Moreover, private space companies (SpaceX Reusable Dragon Lab; Bigelows B330) are also scouting the opportunities of renting or selling modules as platforms for orbital free-flying facilities; modules that can be used for automated fabrication to manned experiments.Topics addressed in the webinar include: 1. Case studies of unique competitive advantages that can be gained from microgravity and space vacuum: wafer reprocessing, fiber optics, crystal growth;2. Prospective solar power orbital data centers;3. Reuse and recycling of orbital debris as a possible feedstock for robotic 3D fabrication potentially in the vacuum as well as inside facilities;4. The story behind the original WakeShield wafer fabrication facility and its relevance to todays activities;5. Energy needs for on-orbit manufacturing6. Environmental value proposition of on-orbit manufacturing for products with toxic byproducts or excessively large green house gases footprints;7. Longer term scenario of flexible, connected, automated, intelligent and sustainable orbital factories of the future.Opening up a less-appreciated aspect of NewSpace, this webinar will be of high interest to CTOs, Directors and Managers from product development to RD, Innovation Strategy leaders, and investors, across many different industrial verticals (materials, electronics, pharmaceuticals, advanced sustainable manufacturing, bioengineering, etc.)and anyone trying to understand what value space can have for their business in the near and far future.

Cozmuta, Ioana↗
DOE OSTI2022

Strong Correspondence in Evapotranspiration and Carbon Dioxide Fluxes Between Different Eddy Covariance Systems Enables Quantification of Landscape Heterogeneity in Dryland Fluxes

Abstract The eddy covariance method is widely used to investigate fluxes of energy, water, and carbon dioxide at landscape scales, providing important information on how ecological systems function. Flux measurements quantify ecosystem responses to environmental perturbations and management strategies, including nature‐based climate‐change mitigation measures. However, due to the high cost of conventional instrumentation, most eddy covariance studies employ a single system, limiting spatial representation to the flux footprint. Insufficient replication may be limiting our understanding of ecosystem behavior. To address this limitation, we deployed eight lower‐cost eddy covariance systems in two clusters around two conventional eddy covariance systems in the Chihuahuan Desert of North America for a period of 2 years. These dryland settings characterized by large temperature variations and relatively low carbon dioxide fluxes represented a challenging setting for eddy covariance. We found very good closure of energy and water balance across all systems (within ±9% of unity). We found very good correspondence between the lower‐cost and conventional systems' fluxes of sensible heat (with concordance correlation coefficient (CCC) of ≥0.87), latent energy (evapotranspiration; CCC ≥ 0.89), and useful correspondence in the net ecosystem exchange ((NEE); with CCC ≥ 0.4) at the daily temporal resolution. Relative to the conventional systems, the low‐frequency systems were characterized by a higher level of random error, particularly in the NEE fluxes. Lower‐cost systems can enable wider deployment affording better replication and sampling of spatiotemporal variability at the expense of greater measurement noise that might be limiting for certain applications. Replicated eddy covariance observations may be useful when addressing gaps in the existing monitoring of critical and underrepresented ecosystems and for measuring areas larger than a single flux footprint.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Consensus and Disagreement in Atmospheric River Detection: ARTMIP Global Catalogues

Atmospheric rivers (ARs) constitute an important mechanism for water vapor transport, but research on their characteristics and impacts has relied on a diverse assortment of detection methodologies, complicating comparisons. The AR Tracking Method Intercomparison Project (ARTMIP) provides a platform for comparing such methodologies, but analysis of ARTMIP catalogues has heretofore focused primarily on specific regions. Here we investigate ARs as detected by an ensemble of algorithms with global coverage. We find that the frequency of occurrence of the majority–consensus ARs produces a robust distribution, featuring five hot spots over the extratropical oceans, against which we compare individual algorithm results. We further explore the underlying similarities and differences via two case studies of AR evolution. The dominant source of disagreement between detection methodologies globally consists of detections (or lack thereof) of weak features, and the algorithms otherwise tend to agree remarkably well on the footprints of ARs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Dynamics of virtual water networks: Role of national socio-economic indicators across the world

Intensified water usage due to rapid industrialization is often dictated by economic policies based on monetary growth rather than sustainable use of environmental resources. In addition, interdependence within economic sectors further interweaves water usage through product transactions, which further makes it difficult to quantify the dynamics of hydro-economic systems at regional, national and global scale. In this study, we investigated the dynamics of domestic virtual water networks (VWN) of 189 countries based on concept of information theory by quantifying network metrics that describes VWN flow capacity, robustness, efficiency and flexibility. These networks represent virtual water interconnected through economic sectors within a specified country built based on environmentally extended multi region input output (EE-MRIO) approach. We further estimated trends associated with network metrics, as well as coupling intensity between metrics with respect to socio-economic indicators, such as, population, Gross Domestic Product (GDP) and Gross National Income (GNI). It was observed that capacity and flexibility of VWNs are strongly and positively correlated indicating that a high capacity VWN can be more flexible. Our results also indicate that, in general a higher percentage of developing countries (i.e. both least developing and developing nations) have exhibited increasing trends in capacity, robustness, efficiency and flexibility of VWN compared to developed nations. It was revealed that the dynamics of VWNs are positively coupled with socio-economic growth for few countries, which indicates the sustainable behavior of VWN with socio-economic growth. Our results argue that the information theory-based metrics by embedding water footprints can holistically capture sustainability aspect of the VWN dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Life-Cycle Analysis of Potentially Longer Life Expectancy CdTe PV Modules

Research on PV module longevity shows that with lower degradation rates and better encapsulation, PV modules can significantly outlast their current life expectancy of 25-30 years. The focus of this study is on alternative CdTe PV module back-contact and encapsulation materials that show the potential of increasing module operation lives from 30 to 40 and 50 years. Life-cycle-analyis shows that some alternative materials may slightly increase cradle-to-gate environmental impacts per m2 of module, but increased operational life more than counterbalances such impacts. The life-cycle carbn footprint of systems operating under average US insolation conditions of 1800 kWh/m2/yr is reduced from 10 gCO2eq/kWh to 6 gCO2eq/kWh when the operation life increases from 30 to 50 yrs. Similar reductions are noted for all life-cycle impact indicators, whereas the EROI of the considered system increases from 67 to 177 as life increases from 30 to 50 yrs.

14 SOLAR ENERGY↗
NASA NTRS2023

The northernmost hyperspectral FLoX sensor dataset for monitoring of high-Arctic tundra vegetation phenology and Sun-Induced Fluorescence (SIF)

A hyperspectral field sensor (FloX) was installed in Adventdalen (Svalbard, Norway) in 2019 as part of the Svalbard Integrated Arctic Earth Observing System (SIOS) for monitoring vegetation phenology and Sun-Induced Chlorophyll Fluorescence (SIF) of high-Arctic tundra. This northernmost hyperspectral sensor is located within the footprint of a tower for long-term eddy covariance flux measurements and is an integral part of an automatic environmental monitoring system on Svalbard (AsMovEn), which is also a part of SIOS. One of the measurements that this hyperspectral instrument can capture is SIF, which serves as a proxy of gross primary production (GPP) and carbon flux rates. This paper presents an overview of the data collection and processing, and the 4-year (2019–2021) datasets in processed format are available at: https://thredds.met.no/thredds/catalog/arcticdata/infranor/NINA-FLOX/raw/catalog.html associated with https://doi.org/10.21343/ZDM7-JD72 under a CC-BY-4.0 license. Results obtained from the first three years in operation showed interannual variation in SIF and other spectral vegetation indices including MERIS Terrestrial Chlorophyll Index (MTCI), EVI and NDVI. Synergistic uses of the measurements from this northernmost hyperspectral FLoX sensor, in conjunction with other monitoring systems, will advance our understanding of how tundra vegetation responds to changing climate and the resulting implications on carbon and energy balance.

hyperspectral field sensor↗
DOE OSTI2024

Precise Motion Control of Hybrid Hydraulic Electric Architecture (HHEA)

Off-highway heavy-duty vehicles have been long-standing users of hydraulic systems for power transmission and control. However, traditional hydraulic systems suffer from significant energy losses which lead to increased operating costs and a larger carbon footprint due to higher CO2 emissions. Improving the efficiency of these mobile machines is crucial not only for reducing their environmental impact but also for saving billions of dollars in operating costs. Currently, the state-of-the-art Load Sensing Architecture uses throttling valves for control, which significantly reduces its efficiency and does not recuperate energy from over-running loads. Researchers have developed several architectures such as Common Pressure Rail systems, Displacement Control, STEAM, and Electrohydraulic Architecture to improve the efficiency of off-road mobile machines. However, each of these architectures has its drawbacks. To increase system efficiency and take advantage of electrification benefits, our research group has developed a novel Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA can significantly improve efficiency, decrease the size of electrical components, and maintain control performance. This new architecture has the potential to revolutionize the off-highway mobile machine industry and lead to a more sustainable future. The HHEA uses a set of common pressure rails to provide the majority of power to the actuators via power-dense hydraulics and uses electric motors for precise control and power modulation. In the context of off-road mobile machines, energy savings are undoubtedly important but it is equally important to consider the machines’ ability to perform tasks with precision and accuracy according to given commands. Therefore, precise motion control is of utmost importance to maintain the utility of Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA presents a unique challenge to motion control due to the discrete pressure changes that occur when the system switches between selected pressure rails. These changes are made to minimize system inefficiencies or to keep the system within the torque capability of the electric motor. Hence, it is important to solve the motion control challenges for HHEA. This thesis aims at developing an effective motion control strategy for HHEA. The dissertation presents a two-tiered control strategy for HHEA, comprising a high-level and a low-level controller. The primary responsibility of the high- level controller is to optimize energy efficiency by making informed pressure rail selections. On the other hand, the low-level controller is focused on achieving precise motion control of the HHEA, which is crucial for realizing the desired reference trajectories. To achieve this, the low-level controller utilizes a passivity-based backstepping integral controller as the nominal control, which handles the motion control between two pressure rail switches. Additionally, a separate least norm controller is utilized as a transition controller to manage motion control during pressure rail transitions. The effectiveness of the combined control strategy is demonstrated through experiments conducted on two hardware-in-the-loop testbeds. Furthermore, the HHEA is installed on the boom and stick actuators of a backhoe arm to build a Human-in-the-Loop system that a human operator can control. A real-time rail switching algorithm is developed to determine pressure rail switching based on present duty cycle information from the operator. Modifications have been made to the human-machine interface to achieve more intuitive control. Modifications include performing control in the task-oriented coordinates, incorporating pressure feedback to enhance control with physical interaction, and using velocity field control to simplify multi-degree-of-freedom tasks and to enable novice operators to perform them with reduced risk, improved efficiency, and productivity. The research in this dissertation makes significant contributions to the field of off-road mobile machine control, providing a novel and effective control strategy for the HHEA, and demonstrating the potential for simplified machine operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗