SEARCH · Engineering Papers

Results for “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.

SourceResearch connectionFrom yearThrough year

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

At least 1,135 records · Page 63

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Future Cost Benefits Analysis for Electrified Vehicles from Advances Due to U.S. Department of Energy Targets

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) supports research and development (R&D), as well as deployment of efficient and sustainable transportation technologies, that will improve energy efficiency and fuel economy and enable America to use less petroleum. To accelerate the creation and adoption of new technologies, DOE-VTO has developed specific targets for a wide range of powertrain technologies (e.g., engine, battery, electric machine, lightweighting, etc.). This paper quantifies the impact of VTO R&D on vehicle energy consumption and cost compared to expected historical improvements across vehicle classes, powertrains, component technologies and timeframes. We have implemented a large scale simulation process to develop and simulate tens of thousands of vehicles on U.S. standard driving cycles using Autonomie, a vehicle simulation tool developed by Argonne National Laboratory. Results demonstrate significant additional reductions in both cost and energy consumption due to the existence of VTO R&D targets compared to predicted historical trends. It is observed that, over time, the fuel consumption of different electrified vehicles is expected to decrease by 40–50% and a reduction of 45–55% for vehicle manufacturing costs owing to significant improvements through various VTO R&D targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Propulsion Electrification Architecture Selection Process and Cost of Carbon Abatement Analysis for Heavy-Duty Off-Road Material Handler

The heavy-duty off-road industry continues to expand efforts to reduce fuel consumption and CO 2 e (carbon dioxide equivalent) emissions. Many manufacturers are pursuing electrification to decrease fuel consumption and emissions. Future policies will likely require electrification for CO2e savings, as seen in light-duty on-road vehicles. Electrified architectures vary widely in the heavy-duty off-road space, with parallel hybrids in some applications and series hybrids in others. The diverse applications for different types of equipment mean different electrified configurations are required. Companies must also determine the value in pursuing electrified architectures; this work analyzes a range of electrified architectures, from micro hybrids to parallel hybrids to series hybrids to a BEV, looking at the total cost, total CO 2 e, and cost per CO 2 e (cost of carbon abatement, or cost of carbon reduction) using data for the year 2021. This study is focused on a heavy-duty off-road material handler, the Pettibone Cary-Lift 204i. This machine’s specialty application, including events like unloading large oil pipes from a railcar, requires a unique electrified architecture that suits its specific needs. However, the results from this study may be extrapolated to similar machinery to inform fuel savings options across the heavy-duty off-road industry. In this study, a unique electrified architecture is determined for the Cary-Lift. This architecture is informed by multiple rounds of a Pugh matrix decision analysis to select a shortened list of desirable electrified architectures. The shortened list is modeled and simulated to determine CO 2 e, cost, and cost per CO 2 e. A final architecture is determined as a plug-in series hybrid that reduces fuel consumption by 65%, targeting the large fuel and CO 2 e savings that are likely to be required for the future of the heavy-duty off-road industry.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Impact of Miller Cycle Strategies on Combustion Characteristics, Emissions and Efficiency in Heavy-Duty Diesel Engines

This study experimentally investigated the potential of Miller cycle strategies as a means to improve fuel consumption and reduce NO x emissions in heavy-duty diesel engines. The experiments were conducted at constant engine speed, load, and engine-out NO x (1160 rev/min, 1.76 MPa net IMEP, 4.5 g/kWh) on a single cylinder research engine equipped with a fully-flexible hydraulic valve train system. Early Intake Valve Closing (EIVC) and Late Intake Valve Closing (LIVC) timing strategies were compared to a conventional intake valve profile. While the decrease in effective compression ratio associated with the use of Miller valve profiles was symmetric around bottom dead center, the decrease in volumetric efficiency (VE) was not. EIVC profiles were more effective at reducing VE than LIVC profiles. Despite this difference, EIVC and LIVC profiles with comparable VE decrease resulted in similar changes in combustion and emissions characteristics. Miller cycle operation at constant intake pressure resulted in lower peak cylinder pressure, higher exhaust temperatures and lower EGR requirements compared to the baseline case, albeit with a significant fuel consumption penalty. Increasing intake manifold pressure to match the baseline air-fuel ratio overcame the fuel consumption penalty, without compromising NO x emissions. Selected EIVC/LIVC profiles were compared to the baseline condition at three different overall turbocharger efficiencies (n TC ). At the baseline n TC , Miller cycle profiles can lower peak cylinder pressures and increase exhaust temperatures with a minimal penalty in BSFC and FSN. At higher n TC than baseline, Miller cycle can maintain the benefits of lower peak cylinder pressure and higher exhaust temperature without a BSFC or FSN penalty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Demonstration of Ego Vehicle and System Level Benefits of Eco-Driving on Chassis Dynamometer

Eco-Driving with connected and automated vehicles has shown potential to reduce energy consumption of an individual (i.e., ego) vehicle by up to 15%. In a project funded by ARPA-E, a team led by Southwest Research Institute demonstrated an 8-12% reduction in energy consumption on a 2017 Prius Prime. This was demonstrated in simulation as well as chassis dynamometer testing. The authors presented a simulation study that demonstrated corridor-level energy consumption improvements by about 15%. This study was performed by modeling a six-kilometer-long urban corridor in Columbus, Ohio for traffic simulations. Five powertrain models consisting of two battery electric vehicles (BEVs), a hybrid electric vehicle (HEV), and two internal combustion engine (ICE) powered vehicles were developed. The design of experiment consisted of sweeps for various levels of traffic, penetration of smart vehicles, penetration of technology, and powertrain electrification. The large-scale simulation study consisted of doing approximately 96,000 powertrain simulations. A sophisticated clustering scheme was built and utilized to down select representative traces for each scenario from the simulation study for vehicle testing on a chassis dynamometer. Furthermore, this paper provides a summary of individual ego vehicle testing as well as a comprehensive overview of the method utilized for down selecting representative traces from large scale simulation studies that can be used to quantify corridor level benefits. Vehicle test results along with corresponding analyses are presented.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2017

Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data

This data set is provided in support of a forthcoming paper: "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," [1]. These files include electricity demand profiles for 200 households randomly selected among the ones available in the 2009 RECS data set for the Midwest region of the United States. The profiles have been generated using the modeling proposed by Muratori et al. [2], [3], that produces realistic patterns of residential power consumption, validated using metered data, with a resolution of 10 minutes. Households vary in size and number of occupants and the profiles represent total electricity use, in watts. The files also include in-home plug-in electric vehicle recharging profiles for 348 vehicles associated with the 200 households assuming both Level 1 (1920 W) and Level 2 (6600 W) residential charging infrastructure. The vehicle recharging profiles have been generated using the modeling proposed by Muratori et al. [4], that produces real-world recharging demand profiles, with a resolution of 10 minutes. [1] M. Muratori, "Impact of uncoordinated plug-in electric vehicle charging on residential power demand." Forthcoming. [2] M. Muratori, M. C. Roberts, R. Sioshansi, V. Marano, and G. Rizzoni, "A highly resolved modeling technique to simulate residential power demand," Applied Energy, vol. 107, no. 0, pp. 465 - 473, 2013. [3] M. Muratori, V. Marano, R. Sioshansi, and G. Rizzoni, "Energy consumption of residential HVAC systems: a simple physically-based model," in 2012 IEEE Power and Energy Society General Meeting. San Diego, CA, USA: IEEE, 22-26 July 2012. [4] M. Muratori, M. J. Moran, E. Serra, and G. Rizzoni, "Highly-resolved modeling of personal transportation energy consumption in the United States," Energy, vol. 58, no. 0, pp. 168-177, 2013.

2009 RECS↗

DOE OSTI2019

DEVELOPING A TRAFFIC SIGNAL ECO-COOPERATIVE ADAPTIVE CRUISE CONTROL SYSTEM FOR BATTERY ELECTRIC VEHICLES

This study developed an eco-driving strategy for battery electric vehicles (BEVs) in the vicinity of signalized intersections, known as BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The system computes a real-time, energy-optimized vehicle trajectory using a BEV vehicle dynamics and energy consumption model. In the proposed approach, the relationship between vehicle speed, acceleration level, and tractive/resistance forces on the vehicle follows the vehicle dynamics model. The Virginia Tech Comprehensive Power-based Electric Vehicle Energy Consumption Model (VT-CPEM) is used to compute the instantaneous battery energy consumption, with the consideration of battery energy regeneration during braking. The Eco-CACC-I energy-optimum trajectory computation is formulated as an optimization problem with constraints. Considering that the optimization solution needs to be computed at a rapid frequency (e.g., 10 Hz) for real-time applications, an A-star algorithm was used here to expedite the computational speed. Lastly, the proposed BEV Eco-CACC-I system was tested in simulation by considering the impacts of various road grades, speed limits, and signal timings. Simulations for an Internal Combustion Engine Vehicles (ICEVs) was conducted to compare with the BEV test results. The results of the comparison indicate that the energy-optimum solution for BEVs is different from that for ICEVs and thus demonstrating the need for vehicle-tailored optimum trajectories.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Energy Demand Management in Buildings Using PCM-Integrated Wall

The buildings in the United States annually consume nearly 40% of total U.S. energy consumption and approximately 75% of U.S. electricity consumption. Almost half of the total U.S. energy consumption in buildings is attributed to the space conditioning through Heating, Ventilation, and Air Conditioning (HVAC) systems. Utilizing thermal energy storage in buildings, particularly integrating phase change material (PCM) in the walls, has been reported to be an effective method of managing the space heating and cooling loads. This presentation covers an in-depth discussion on the integration of a PCM to building walls, the key conditions required for effective utilization of the PCM, and effect of the PCM transition temperature and the PCM location on energy-saving potential of the PCM-integrated wall.

building↗

DOE OSTI2023

Efficient Air Dehumidification Can Save 15%-50% of Cooling Energy in Commercial Buildings

Current approach to dehumidification in commercial buildings with chilled/hot water AHU systems is to overcool return + supply air to dewpoint, and then reheat before supply to zone. This is energy inefficient, with reheat often being gas-fired. To reduce energy consumption, building operators will often operate at little-to-no outside air, sacrificing IAQ. Decarbonizing commercial buildings requires solutions to reduce and fully electrify dehumidification energy consumption. The Altaire ADAPT and Conservant HEDS systems aim to solve this problem by decoupling humidity control from cooling reduces energy consumption while enabling improved IAQ management.

commercial buildings↗

DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

actuated signal control↗

DOE OSTI2024

Gaining Real-Time Water Leak Detection

Devens Reserve Forces Training Area is a United States Army Reserve (USAR) Installation that struggles with severe water leaks, often causing significant damage to the facility and requiring major renovation. Traditional water use is highly dependent on occupancy, so it can be difficult to benchmark a facility’s water use. It can be exceptionally difficult when occupancy is transient and/or varies. Pacific Northwest National Laboratory (PNNL) collaborated with Devens to implement real-time monitoring of their water consumption by utilizing the smart meter data from their existing 23 water meters. PNNL created a simple algorithm to calculate hourly water consumption and trigger an alert to be instantly emailed to Devens’ personnel when there appears to be a water leak in any building with a smart water meter. Here, this approach is expected to save hundreds of thousands of dollars in unnecessary water consumption costs and damages from leaks and was implemented with little-to-no costs or service disruptions. Next steps for this project include slow leak detection through nighttime monitoring and to extrapolate this water leak approach to the remainder 360 water meters on USAR’s Enterprise Building Control System so USAR sites across the country can be instantly notified of potential water leaks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Low-Temperature Plasma Assisted Kinetics Study of Ethanol

Abstract: Non- equilibrium plasma assisted kinetics of ethanol at 0.5 atm over a temperature range of 523-1203 K were studied at stoichiometric conditions by using a plasma flow reactor (PFR). The effects of plasma chemistry on fuel and its influence on neutral chemistry is decoupled with both experimental and modelling efforts. Enhanced reactivity was observed experimentally in both plasma-assisted oxidation and pyrolysis cases with fuel consumption beginning at temperatures as low as 523 K. Absolute fuel consumption was observed at temperatures nearly 200 K earlier than pure thermal reactions highlighting the effectiveness of non-equilibrium plasma to promote reactivity. Modelling results illustrated the effect of electron impact reactions towards accelerating fuel consumption and promoting low temperature chemistry by generating excited state N2 and reactive O and OH radicals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Validating Savings Claims of Cold Climate Zero Energy Ready Homes

This report details the validation methods used to analyze consumption at each of these homes. It includes a detailed end-use examination of consumptions from the following categories: 1) Heating, 2) Cooling, 3) Lights, Appliances, and Miscellaneous Electric Loads (LAMELS) along with Domestic Hot Water Use, 4) Ventilation, and 5) PV generation. A utility bill disaggregation method, which allows a crude estimation of space conditioning loads based on outdoor air temperature, was also performed and the results compared to the actual measured data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Enabling energy‐efficient manufacturing of pharmaceutical solid oral dosage forms via integrated techno‐economic analysis and advanced process modeling

Abstract The global pharmaceutical industry is a trillion‐dollar market. However, the pharmaceutical sector often lags in manufacturing innovation and automation which limits its potential to maximize energy efficiency. The integration of techno‐economic analysis (TEA) with advanced process models as part of an overarching smart manufacturing platform, can help industries create business models, which can be adapted for manufacturing to reduce energy consumption and operating costs while ensuring product quality which can further enable a more sustainable process operation. In this study, a rational design of experiment on three unit‐operations (wet granulation, drying, and milling) was performed on a batch (case 1) and continuous (case 2) pharmaceutical process to obtain experimental data. Process models for predicting product quality and energy efficiency of each of the three‐unit operations were developed. The experimental data were used to validate the models and good agreement was observed. The energy consumption of each unit operation was calculated using statistical models relating the power consumption and the process parameters. The developed process models and energy models were further integrated into a TEA framework, which quantified the energy and monetary cost of manufacturing for both batch and continuous manufacturing cases. With this integrated framework, energy costs savings of ~33% was obtained in the continuous manufacturing process (case 2) over the batch process (case 1).

Sampat, Chaitanya↗

DOE OSTI2014

Investigation of thermochemical biorefinery sizing and environmental sustainability impacts for conventional supply system and distributed pre-processing supply system designs

The 2011 US Billion-Ton Update estimates that by 2030 there will be enough agricultural and forest resources to sustainably provide at least one billion dry tons of biomass annually, enough to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefinery capacity, which, in turn, depend upon economic value, feedstock logistics, and sustainability. A cross-functional team has examined combinations of advances in feedstock supply systems and biorefinery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable biomass availability. A previous report on biochemical refinery capacity noted that under advanced feedstock logistic supply systems that include depots and pre-processing operations there are cost advantages that support larger biorefineries up to 10 000 DMT/day facilities compared to the smaller 2000 DMT/day facilities. This report focuses on analyzing conventional versus advanced depot biomass supply systems for a thermochemical conversion and refinery sizing based on woody biomass. The results of this analysis demonstrate that the economies of scale enabled by advanced logistics offsets much of the added logistics costs from additional depot processing and transportation, resulting in a small overall increase to the minimum ethanol selling price compared to the conventional logistic supply system. While the overall costs do increase slightly for the advanced logistic supply systems, the ability to mitigate moisture and ash in the system will improve the storage and conversion processes. In addition, being able to draw on feedstocks from further distances will decrease the risk of biomass supply to the conversion facility.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Impacts of intentional mycoplasma contamination on CHO cell bioreactor cultures

Mycoplasma contamination events in biomanufacturing facilities can result in loss of production and costly cleanups. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and may penetrate the 0.2 µm filters often used in the primary clarification of harvested cell culture fluid. Culture cell-based and indicator cell-based assays that are used to detect mycoplasma are highly sensitive but can take up to 28 days to complete and cannot be used for real-time decision making during the biomanufacturing process. To support real-time measurements of mycoplasma contamination, there is a push to explore nucleic acid testing. However, cell-based methods measure growth or colony forming units and nucleic acid testing measures genome copy number; this has led to ambiguity regarding how to compare the sensitivity of the methods. In addition, the high risk of conducting experiments wherein one deliberately spikes mycoplasma into bioreactors has dissuaded commercial groups from performing studies to explore the multiple variables associated with the upstream effects of a mycoplasma contamination in a manufacturing setting. Here we studied the ability of Mycoplasma arginini to persist in a single-use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G1 (IgG1) antibody. We examined M. arginini growth and detection by culture methods, as well as the effects of M. arginini on mammalian cell health, metabolism, and productivity. We compared process parameters and controls normally measured in bioreactors including dissolved oxygen, gas mix, and base addition to maintain pH, to examine parameter changes as potential indicators of contamination. Our work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Importantly, how the M. arginini contamination impacts the CHO cells is influenced by the concentration of CHO cells and rate of perfusion at the time of M. arginini spike. Careful evaluation of dissolved oxygen, pH control parameters, ammonia, and arginine over time may be used to indicate Mycoplasma contamination events in biomanufacturing facilities can result in loss of production and costly cleanups. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and may penetrate the 0.2 µm filters often used in the primary clarification of harvested cell culture fluid. Culture cell-based and indicator cell-based assays that are used to detect mycoplasma are highly sensitive but can take up to 28 days to complete and cannot be used for real-time decision making during the biomanufacturing process. To support real-time measurements of mycoplasma contamination, there is a push to explore nucleic acid testing. However, cell-based methods measure growth or colony forming units and nucleic acid testing measures genome copy number; this has led to ambiguity regarding how to compare the sensitivity of the methods. In addition, the high risk of conducting experiments wherein one deliberately spikes mycoplasma into bioreactors has dissuaded commercial groups from performing studies to explore the multiple variables associated with the upstream effects of a mycoplasma contamination in a manufacturing setting. Here we studied the ability of Mycoplasma arginini to persist in a single-use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G1 (IgG1) antibody. We examined M. arginini growth and detection by culture methods, as well as the effects of M. arginini on mammalian cell health, metabolism, and productivity. We compared process parameters and controls normally measured in bioreactors including dissolved oxygen, gas mix, and base addition to maintain pH, to examine parameter changes as potential indicators of contamination. Our work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Importantly, how the M. arginini contamination impacts the CHO cells is influenced by the concentration of CHO cells and rate of perfusion at the time of M. arginini spike. Careful evaluation of dissolved oxygen, pH control parameters, ammonia, and arginine over time may be used to indicate Mycoplasma contamination events in biomanufacturing facilities can result in loss of production and costly cleanups. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and may penetrate the 0.2 µm filters often used in the primary clarification of harvested cell culture fluid. Culture cell-based and indicator cell-based assays that are used to detect mycoplasma are highly sensitive but can take up to 28 days to complete and cannot be used for real-time decision making during the biomanufacturing process. To support real-time measurements of mycoplasma contamination, there is a push to explore nucleic acid testing. However, cell-based methods measure growth or colony forming units and nucleic acid testing measures genome copy number; this has led to ambiguity regarding how to compare the sensitivity of the methods. In addition, the high risk of conducting experiments wherein one deliberately spikes mycoplasma into bioreactors has dissuaded commercial groups from performing studies to explore the multiple variables associated with the upstream effects of a mycoplasma contamination in a manufacturing setting. Here we studied the ability of Mycoplasma arginini to persist in a single-use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G1 (IgG1) antibody. We examined M. arginini growth and detection by culture methods, as well as the effects of M. arginini on mammalian cell health, metabolism, and productivity. We compared process parameters and controls normally measured in bioreactors including dissolved oxygen, gas mix, and base addition to maintain pH, to examine parameter changes as potential indicators of contamination. Our work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Importantly, how the M. arginini contamination impacts the CHO cells is influenced by the concentration of CHO cells and rate of perfusion at the time of M. arginini spike. Careful evaluation of dissolved oxygen, pH control parameters, ammonia, and arginine over time may be used to indicate mycoplasma contamination in CHO cell cultures in a bioreactor before a read-out from a traditional method.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2012

Achieving energy efficiency during collective communications

Energy consumption has become a major design constraint in modern computing systems. With the advent of petaflops architectures, power-efficient software stacks have become imperative for scalability. Techniques such as dynamic voltage and frequency scaling (called DVFS) and CPU clock modulation (called throttling) are often used to reduce the power consumption of the compute nodes. To avoid significant performance losses, these techniques should be used judiciously during parallel application execution. For example, its communication phases may be good candidates to apply the DVFS and CPU throttling without incurring a considerable performance loss. They are often considered as indivisible operations although little attention is being devoted to the energy saving potential of their algorithmic steps. In this work, two important collective communication operations, all-to-all and allgather, are investigated as to their augmentation with energy saving strategies on the per-call basis. The experiments prove the viability of such a fine-grain approach. They also validate a theoretical power consumption estimate for multicore nodes proposed here. While keeping the performance loss low, the obtained energy savings were always significantly higher than those achieved when DVFS or throttling were switched on across the entire application run

36 MATERIALS SCIENCE↗

DOE OSTI2019

Life Cycle Analysis of Decentralized Preprocessing Systems for Fast Pyrolysis Biorefineries with Blended Feedstocks in the Southeastern United States

Blending biomass feedstock is an enticing approach to mitigate supply chain risks that are common challenges for large-scale biomass utilization. Understanding the potential environmental benefits of biofuels produced from blended biomass and identifying driving parameters are critical for the supply chain design. Herein, a cradle-to-gate life cycle analysis model for fast pyrolysis biorefineries converting blended feedstocks (pine residues and switchgrass) with traditional centralized and alternative decentralized preprocessing sites, so-called depots, is explained. Different scenarios are developed to investigate the impacts of parameters such as feedstock blending ratios, biorefinery and depot capacities, preprocessing technologies, and allocation methods. The life-cycle energy consumption and global warming potential (GWP) of biofuel production with depots vary between 0.7–1.1 MJ MJ -1 and 43.2–76.6 g CO 2 eq. MJ -1 , respectively. The results are driven by biorefinery processes and depot preprocesses. A decentralized design reduces the energy consumption of the biorefinery but increases the overall life-cycle energy and GWP. Such increases can be significantly mitigated by increasing switchgrass content as the energy consumption at the depot is driven largely by the higher moisture content of pine feedstocks. Allocation methods have a further impact on the results but do not change the major trends and overall conclusions.

09 BIOMASS FUELS↗

DOE OSTI2020

Microwave‐assisted hydrodistillation of the essential oil from Algerian Pimpinella anisum seeds

Abstract Essential oils (EOs) from anise seeds ( Pimpinella anisum ) collected in the Algerian region were extracted by microwave‐assisted hydrodistillation (MAHD) and hydrodistillation (HD). The oil yield (%), chemical composition, energetic consumption and the antimicrobial properties were evaluated of the obtained EO. The yields obtained by both processes were 2.81 ± 0.01% for 90 minutes and 3.30 ± 0.05% for 330 minutes for MAHD and HD, respectively. The determination of the chemical composition of EOs by GC‐MS revealed the presence of a majority compound, trans ‐anethole 81.52% and 91.31% for MAHD and HD, respectively. The other main compounds present in the oils for MAHD and HD were, respectively: methyl chavicol (estragole) (0.63%‐1.39%), cis ‐anethole (0.23%‐0.34%), anisaldehyde (1.1%‐1.57%), anisyl methyl ketone (0.28%‐0.13%), trans ‐methyl isoellgenol (0.31%‐0.17%), γ ‐himachalene (0.5%‐0.36%), trans ‐pseudoisoeugenyl 2‐methylbutyrate (6.53%‐2.53%) and epoxy‐pseudoisoeugenyl 2‐methylbutyrate (2.01%‐0.56%). The EO obtained by MAHD detected other compounds, fenchone 0.41%, limonene 0.68%, cis ‐jasmolacatone extra C 0.41%, trans ‐isolongifolanone 0.2% and α ‐himachalene 0.16%. The energetic consumption by MAHD was significantly less than HD. Theoretical data from mathematical modelling were compared with practical data, and the coefficient of determination was between 0.93 and 0.97. The sensibility of bacterial strains to the essential oil obtained by MAHD is marked relatively to that obtained by HD, and for the sensibility of fungal strains, it was conserved. The MAHD process revealed a good yield of anise seeds EOs while reducing extraction time and energetic consumption. The EO extracted by this process revealed the presence of other compounds while improving antibacterial activity.

Boumahdi, Yamina↗