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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Tea consumption and risk of bladder cancer in the Bladder Cancer Epidemiology and Nutritional Determinants (BLEND) Study: Pooled analysis of 12 international cohort studies

Tea has been shown to be associated with reduced risk of several diseases including cardiovascular diseases, stroke, metabolic syndrome, and obesity. However, the results on the relationship between tea consumption and bladder cancer are conflicting. This research aimed to assess the association between tea consumption and risk of bladder cancer using a pooled analysis of prospective cohort data. Individual data from 532,949 participants in 12 cohort studies, were pooled for analyses. Cox regression models stratified by study centre was used to estimate hazard ratios (HR) and corresponding 95% CIs. Fractional polynomial regression models were used to examine the dose–response relationship. A higher level of tea consumption was associated with lower risk of bladder cancer incidence (compared with no tea consumption: HR = 0.87, 95% C.I. = 0.77–0.98 for low consumption; HR = 0.86, 95% C.I. = 0.77–0.96 for moderate consumption; HR = 0.84, 95% C.I. = 0.75–0.95 for high consumption). When stratified by sex and smoking status, this reduced risk was statistically significant among men and current and former smokers. In addition, dose–response analyses showed a lower bladder cancer risk with increment of 100 ml of tea consumption per day (HR-increment = 0.97; 95% CI = 0.96–0.98). A similar inverse association was found among males, current and former smokers while never smokers and females showed non-significant results, suggesting potential sex-dependent effect. Higher consumption of tea is associated with reduced risk of bladder cancer with potential interaction with sex and smoking status. Further studies are needed to clarify the mechanisms for a protective effect of tea (e.g. inhibition of the survival and proliferation of cancer cells and anti-inflammatory mechanisms) and its interaction with smoking and sex.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2012

Optimal Dynamic Sub-Threshold Technique for Extreme Low Power Consumption for VLSI

For miniaturization of electronics systems, power consumption plays a key role in the realm of constraints. Considering the very large scale integration (VLSI) design aspect, as transistor feature size is decreased to 50 nm and below, there is sizable increase in the number of transistors as more functional building blocks are embedded in the same chip. However, the consequent increase in power consumption (dynamic and leakage) will serve as a key constraint to inhibit the advantages of transistor feature size reduction. Power consumption can be reduced by minimizing the voltage supply (for dynamic power consumption) and/or increasing threshold voltage (V(sub th), for reducing leakage power). When the feature size of the transistor is reduced, supply voltage (V(sub dd)) and threshold voltage (V(sub th)) are also reduced accordingly; then, the leakage current becomes a bigger factor of the total power consumption. To maintain low power consumption, operation of electronics at sub-threshold levels can be a potentially strong contender; however, there are two obstacles to be faced: more leakage current per transistor will cause more leakage power consumption, and slow response time when the transistor is operated in weak inversion region. To enable low power consumption and yet obtain high performance, the CMOS (complementary metal oxide semiconductor) transistor as a basic element is viewed and controlled as a four-terminal device: source, drain, gate, and body, as differentiated from the traditional approach with three terminals: i.e., source and body, drain, and gate. This technique features multiple voltage sources to supply the dynamic control, and uses dynamic control to enable low-threshold voltage when the channel (N or P) is active, for speed response enhancement and high threshold voltage, and when the transistor channel (N or P) is inactive, to reduce the leakage current for low-leakage power consumption.

Duong, Tuan A.↗
NASA NTRS2012

Sensitivity of Mission Energy Consumption to Turboelectric Distributed Propulsion Design Assumptions on the N3-X Hybrid Wing Body Aircraft

In a previous study by the authors it was shown that the N3-X, a 300 passenger hybrid wing body (HWB) aircraft with a turboelectric distributed propulsion (TeDP) system, was able to meet the NASA Subsonic Fixed Wing (SFW) project goal for N+3 generation aircraft of at least a 60% reduction in total energy consumption as compared to the best in class current generation aircraft. This previous study combined technology assumptions that represented the highest anticipated values that could be matured to technology readiness level (TRL) 4-6 by 2030. This paper presents the results of a sensitivity analysis of the total mission energy consumption to reductions in each key technology assumption. Of the parameters examined, the mission total energy consumption was most sensitive to changes to total pressure loss in the propulsor inlet. The baseline inlet internal pressure loss is assumed to be an optimistic 0.5%. An inlet pressure loss of 3% increases the total energy consumption 9%. However changes to reduce inlet pressure loss can result in additional distortion to the fan which can reduce fan efficiency or vice versa. It is very important that the inlet and fan be analyzed and optimized as a single unit. The turboshaft hot section is assumed to be made of ceramic matrix composite (CMC) with a 3000 F maximum material temperature. Reducing the maximum material temperature to 2700 F increases the mission energy consumption by only 1.5%. Thus achieving a 3000 F temperature in CMCs is important but not central to achieving the energy consumption objective of the N3-X/TeDP. A key parameter in the efficiency of superconducting motors and generators is the size of the superconducting filaments in the stator. The size of the superconducting filaments in the baseline model is assumed to be 10 microns. A 40 micron filament, which represents current technology, results in a 200% increase in AC losses in the motor and generator stators. This analysis shows that for a system with 40 micron filaments the higher stator losses plus the added weight and power of larger cryocoolers results in a 4% increase in mission energy consumption. If liquid hydrogen is used to cool the superconductors the 40 micron fibers results in a 200% increase in hydrogen required for cooling. Each pound of hydrogen used as fuel displaces 3 pounds of jet fuel. For the N3-X on the reference mission the additional hydrogen due to the increase stator losses reduces the total fuel weight 10%. The lighter fuel load and attendant vehicle resizing reduces the total energy consumption more than the higher stator losses increase it. As a result with hydrogen cooling there is a slight reduction in mission energy consumption with increasing stator losses. This counter intuitive result highlights the need to consider the full system impact of changes rather than just at the component or subsystem level.

Felder, James L.↗
DOE OSTI2016

Learning to REDUCE: A Reduced Electricity Consumption Prediction Ensemble

Utilities use Demand Response (DR) to balance supply and demand in the electric grid by involving customers in efforts to reduce electricity consumption during peak periods. To implement and adapt DR under dynamically changing conditions of the grid, reliable prediction of reduced consumption is critical. However, despite the wealth of research on electricity consumption prediction and DR being long in practice, the problem of reduced consumption prediction remains largely un-addressed. In this paper, we identify unique computational challenges associated with the prediction of reduced consumption and contrast this to that of normal consumption and DR baseline prediction.We propose a novel ensemble model that leverages different sequences of daily electricity consumption on DR event days as well as contextual attributes for reduced consumption prediction. We demonstrate the success of our model on a large, real-world, high resolution dataset from a university microgrid comprising of over 950 DR events across a diverse set of 32 buildings. Our model achieves an average error of 13.5%, an 8.8% improvement over the baseline. Our work is particularly relevant for buildings where electricity consumption is not tied to strict schedules. Our results and insights should prove useful to the researchers and practitioners working in the sustainable energy domain.

Aman, Saima↗
DOE OSTI2017

A thorough assessment of China’s standard for energy consumption of buildings

China's Design Standard for Energy Efficiency of Public Buildings (the Design Standard) is widely used in the design phase to regulate the energy efficiency of physical assets (envelope, lighting, HVAC) in buildings. However, the standard does not consider many important factors that influence the actual energy use in buildings, and this can lead to gaps between the design estimates and actual energy consumption. To achieve the national energy savings targets defined in the strategic 12th Five-Year Plan, China developed the first standard for energy consumption of buildings GB/T51161-2016 (the Consumption Standard). This study provides an overview of the Consumption Standard, identifies its strengths and weaknesses, and recommends future improvements. The analysis and discussion of the constraint value and the leading value, two key indicators of the energy use intensity, provide insight into the intent and effectiveness of the Consumption Standard. The results indicated that consistency between China's Design Standard GB 50189-2015 and the Consumption Standard GB/T51161-2016 could be achieved if the Design Standard used the actual building operations and occupant behavior in calculating the energy use in Chinese buildings. The development of an outcome-based code in the U.S. was discussed in comparison with China's Consumption Standard, and this revealed the strengths and challenges associated with implementing a new compliance method based on actual energy use in buildings in the U.S. Overall, this study provides important insights into the latest developments of actual consumption-based building energy standards, and this information should be valuable to building designers and energy policy makers in China and the U.S.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A Review and Outlook on Energy Consumption Estimation Models for Electric Vehicles

Electric vehicles (EVs) are critical to the transition to a low-carbon transportation system. The successful adoption of EVs heavily depends on energy consumption models that can accurately and reliably estimate electricity consumption. This paper reviews the state-of-the-art of EV energy consumption models, aiming to provide guidance for future development of EV applications. Here, we summarize influential variables of EV energy consumption into four categories: vehicle component, vehicle dynamics, traffic and environment related factors. We classify and discuss EV energy consumption models in terms of modeling scale (microscopic vs. macroscopic) and methodology (data-driven vs. rule-based). Our review shows trends of increasing macroscopic models that can be used to estimate trip-level EV energy consumption and increasing data-driven models that utilized machine learning technologies to estimate EV energy consumption based on large volume real-world data. We identify research gaps for EV energy consumption models, including the development of energy estimation models for modes other than personal vehicles (e.g., electric buses, electric trucks, and electric non-road vehicles); the development of energy estimation models that are suitable for applications related to vehicle-to-grid integration; and the development of multi-scale energy estimation models as a holistic modeling approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Automated vehicle microscopic energy consumption study (AV-Micro): Data collection and model development

While the Adaptive Cruise Control (ACC) system in automated vehicles (AVs) is expected to impact transportation energy significantly, existing AV energy consumption models only directly adopt those developed with Human-driven Vehicle (HV) data without even slight adaptation or calibration to accommodate unique AV energy consumption features. This study will investigate how accurately HV data-based models can predict the energy consumption of AVs. Empirical trajectory data and corresponding instantaneous energy consumption rates from both AVs and HVs were collected. We adopted two classical HV data-based models to fit these data. The calibration results indicated that these models yield around 20 30% prediction errors for AVs. To further improve the prediction accuracy, this study designed an AV-Micro model by incorporating components of multiple classic energy consumption models that better capture ACC energy consumption features, including piecewise driving behavior. With this, the AV-Micro model achieves lower than 10% prediction errors. The AV-Micro model’s high consistency across different test runs was verified with statistical significance tests, demonstrating its adaptability in different driving profiles. To confirm the discrepancies between the energy consumption features of AVs and HVs, more statistical significance tests were conducted to show that the AV-Micro model cannot be directly applied to HV data. The findings by calibrated AV-Micro models revealed that AVs consume approximately 80.5–146.4 J more energy than HVs for each meter traveled. Furthermore, the frequency analysis of energy consumption indicates that there is still some room for AVs to improve energy efficiency, particularly given their larger amplitude high-frequency fluctuations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Impact of Non-Steady State Operation on Cooling Water Consumption at Coal- and Natural Gas-Fired Power Plants

Increased renewable energy penetration in the electricity grid in coming decades will result in more frequent cycling at thermal power plants. Simultaneously, thermal power plants may face water scarcity with declining availability of cooling water. Therefore, to enhance thermal power plants’ resiliency to water shortages it is important to understand how non-steady conditions due to cycling will impact cooling water consumption and withdrawal intensity. Non-steady operation at power plants has been previously shown to decrease power plant thermal efficiency. Energy balance models have also demonstrated that a decrease in thermal efficiency is expected to increase cooling water consumption intensity. Furthermore, past work has used operating hours data to show idling and cycling gaps where cooling systems operate more than corresponding generators. As a result, an increase in cycling behavior may impact cooling water consumption and withdrawal intensity. This study uses data from the Energy Information Administration (EIA) and Environmental Protection Agency (EPA) to quantify the impact of cycling cooling water consumption intensity for recirculating cooling systems and withdrawal intensity for once-through cooling systems using energy balance and statistical approaches. In a novel application of a fixed effects model to study the effect of temperature on cooling water consumption and withdrawal intensity, this study finds temperature was consistently expected to increase consumption intensity and withdrawal intensity. Non-steady state conditions do not increase cooling water consumption intensity with statistical significance across unit types. However, additional validation of cooling water data is required to confirm these observed trends due to the sensitivity of these findings to model form and concerns with data quality of the dependent variables, cooling water consumption and withdrawal.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Evaluation of Oxygen Consumption as a Sensitive Measure of Electrical Cable Polymer Insulation Degradation

Polymers used as dielectric materials in nuclear grade electrical cables, such as cross-linked polyethylene (XLPE) and ethylene-propylene rubber (EPR), are long-lived and durable. Estimating the decades-long useful service life of polymers experimentally in a feasible timeframe of weeks or months requires greatly accelerated aging in the laboratory at elevated temperatures and/or gamma dose rates. Many limitations of accelerated aging, such as due to artefacts of the process including diffusion limited oxidation and dose rate effects, have been identified that can make accurate lifetime prediction at service conditions challenging. This can be due to differences in degradation mechanisms between rapid and extended aging or to the presence of induction periods during which early aging is undetectable using common metrics of polymer insulation characterization such as tensile elongation at break. Conceptually, an ideal measure of aging would track clearly and predictably with material changes throughout the lifecycle of the evolving material state from early aging through end of useful life. With such a metric accelerated aging could be performed at much milder conditions, conditions closer to those found in long term service, and end of life calculated from the early data. Oxygen consumption has previously been proposed as a sensitive measure of insulation polymer oxidation that might meet such desirable characteristics. In this work, nuclear cable insulation samples of the two most common types, XLPE and EPR, from two of the most sourced manufacturers, RSCC and The Okonite Company, were subjected to gamma irradiation at dose rates of 100, 200, and 300 Gy/hr for up to 42 days at 26°C. The aged samples were used to evaluate oxygen consumption as a sensitive measure of aging for these materials and these conditions. For comparison and validation, the aged samples were also characterized using the more conventional tests of mass change, density, carbonyl index, and yellowness index. For both materials, oxygen consumption during irradiation was found to track consistently with applied dose—oxygen consumption rate was linear with time. Mass change and carbonyl index were also clearly proportional to exposure dose. Yellowness index, a surface sensitive measure, was observed to increase linearly with dose at low exposure levels before plateauing. Sample density was not observed to change under the conditions explored. Oxygen consumption was found to be a particularly sensitive metric to measure the degradation of polymeric cable insulation exposed to radiation. Oxygen consumption was compared to Arrhenius and time-temperature-superposition methods for activation energy calculation using literature date and found to be a useful and viable alternative for lifetime prediction. The techniques developed in this work are anticipated to be valuable in the estimation of insulation aging rates under mild conditions approaching service conditions. Direction comparison of useful life prediction by oxygen consumption with prediction via Arrhenius methodology for thermal aging and existing methods for radiation and combined thermal/radiation aging would serve to further validate this promising approach and refine our understanding of material-specific aging rates.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Impact of Intersection Control on Battery Electric Vehicle Energy Consumption

Battery electric vehicle (BEV) sales have significantly increased in recent years. They have different energy consumption patterns compared to the fuel consumption patterns of internal combustion engine vehicles (ICEVs). This study quantified the impact of intersection control approaches—roundabout, traffic signal, and two-way stop controls—on BEVs’ energy consumption. The paper systematically investigates BEVs’ energy consumption patterns compared to the fuel consumption of ICEVs. The results indicate that BEVs’ energy consumption patterns are significantly different than ICEVs’ patterns. For example, for BEVs approaching a high-speed intersection, the roundabout was found to be the most energy-efficient intersection control, while the two-way stop sign was the least efficient. In contrast, for ICEVs, the two-way stop sign was the most fuel-efficient control, while the roundabout was the least efficient. Findings also indicate that the energy saving of traffic signal coordination was less significant for BEVs compared to the fuel consumption of ICEVs since more regenerative energy is produced when partial or poorly coordinated signal plans are implemented. The study confirms that BEV regenerative energy is a major factor in energy efficiency, and that BEVs recover different amounts of energy in different urban driving environments. The study suggests that new transportation facilities and control strategies should be designed to enhance BEVs’ energy efficiency, particularly in zero emission zones.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Effect Of Platooning on Fuel Consumption of Class 8 Vehicles Over a Range of Speeds, Following Distances, and Mass

This research project evaluates fuel consumption results of two Class 8 tractor-trailer combinations platooned together compared to their standalone fuel consumption. A series of ten modified SAE Type II J1321 fuel consumption track tests were performed to document fuel consumption of two platooned vehicles and a control vehicle at varying steady-state speeds, following distances, and gross vehicle weights (GVWs). The steady-state speeds ranged from 55 mph to 70 mph, the following distances ranged from a 20-ft following distance to a 75-ft following distance, and the GVWs were 65K lbs and 80K lbs. All tractors involved had U.S. Environmental Protection Agency (EPA) SmartWay-compliant aerodynamics packages installed, and the trailers were equipped with side skirts. Effects of vehicle speed, following distance, and GVW on fuel consumption were observed and analyzed. The platooning demonstration system used in this study consisted of radar systems, Dedicated Short-Range Communication (DSRC) vehicle-to-vehicle (V2V) communications, vehicle braking and torque control interface, cameras and driver displays. The lead tractor consistently demonstrated an improvement in average fuel consumption reduction as following distance decreased, with results showing 2.7% to 5.3% fuel savings at a GVW of 65k. The trailing vehicle achieved fuel consumption savings ranging from 2.8% to 9.7%; tests during which the engine cooling fan did not operate achieved savings of 8.4% to 9.7%. 'Team' fuel savings, considering the platooned vehicles as one, ranged from 3.7% to 6.4%, with the best combined result being for 55 mph, 30-ft following distance, and 65k GVW.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Inconsistent Investment and Consumption Problems

In a traditional Black–Scholes market we develop a verification theorem for a general class of investment and consumption problems where the standard dynamic programming principle does not hold. The theorem is an extension of the standard Hamilton–Jacobi–Bellman equation in the form of a system of non-linear differential equations. We derive the optimal investment and consumption strategy for a mean-variance investor without pre-commitment endowed with labor income. In the case of constant risk aversion it turns out that the optimal amount of money to invest in stocks is independent of wealth. The optimal consumption strategy is given as a deterministic bang-bang strategy. In order to have a more realistic model we allow the risk aversion to be time and state dependent. Of special interest is the case were the risk aversion is inversely proportional to present wealth plus the financial value of future labor income net of consumption. Using the verification theorem we give a detailed analysis of this problem. It turns out that the optimal amount of money to invest in stocks is given by a linear function of wealth plus the financial value of future labor income net of consumption. The optimal consumption strategy is again given as a deterministic bang-bang strategy. We also calculate, for a general time and state dependent risk aversion function, the optimal investment and consumption strategy for a mean-standard deviation investor without pre-commitment. In that case, it turns out that it is optimal to take no risk at all.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Rapid kinetics of changes in oxygen consumption rate in thrombin-stimulated platelets measured by high-resolution respirometry

Highlights: • High resolution respirometry can be used to investigate the rapid kinetics of changes in platelet oxygen consumption rate. • Thrombin triggers a rapid, transient increase in platelet oxygen consumption rate. • Aspirin and oligomycin partially inhibit the increased oxygen consumption rate. Platelet activation plays a key role in normal haemostasis and pathological thrombosis. Platelet activation is rapid; within minutes of stimulation, platelets generate bioactive phospholipids, secrete their granule contents, activate integrins and aggregate together to form a haemostatic plug. These events are dependent on ATP synthesis. Mitochondrial function in platelets from healthy volunteers and patients with a range of diseases indicate an important role for oxygen consumption in oxidative phosphorylation in normal and pathological function. Platelets also consume oxygen during oxidation reactions, such as cyclooxygenase-dependent thromboxane A{sub 2} synthesis. In this study, we used high-resolution respirometry to investigate rapid changes in oxygen consumption during platelet activation. We demonstrated a rapid, transient increase in oxygen consumption rate within minutes of platelet stimulation by the physiological activator, thrombin. This was partly inhibited by aspirin and by oligomycin. This shows that high resolution respirometry can provide information regarding rapid and dynamic changes in oxygen consumption during platelet activation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Characterizing, Modeling, and Accurately Simulating Power and Energy Consumption of I/O-intensive Scientific Workflows

While distributed computing infrastructures can provide infrastructure-level techniques for managing energy consumption, application-level energy consumption models have also been developed to support energy-efficient scheduling and resource provisioning algorithms. In this work, we analyze the accuracy of a widely-used application-level model that has been developed and used in the context of scientific workflow executions. To this end, we profile two production scientific workflows on a distributed platform instrumented with power meters. We then conduct an analysis of power and energy consumption measurements. This analysis shows that power consumption is not linearly related to CPU utilization and that I/O operations significantly impact power, and thus energy, consumption. We then propose a power consumption model that accounts for I/O operations, including the impact of waiting for these operations to complete, and for concurrent task executions on multi-socket, multi-core compute nodes. We implement our proposed model as part of a simulator that allows us to draw direct comparisons between real-world and modeled power and energy consumption. Here, we find that our model has high accuracy when compared to real-world executions. Furthermore, our model improves accuracy by about two orders of magnitude when compared to the traditional models used in the energy-efficient workflow scheduling literature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Primary and secondary battery consumption trends in Sweden 1996–2013: Method development and detailed accounting by battery type

Highlights: • Developed MFA method was validated by the national statistics. • Exponential increase of EEE sales leads to increase in integrated battery consumption. • Digital convergence is likely to be a cause for primary batteries consumption decline. • Factors for estimation of integrated batteries in EE are provided. • Sweden reached the collection rates defined by European Union. - Abstract: In this article, a new method based on Material Flow Accounting is proposed to study detailed material flows in battery consumption that can be replicated for other countries. The method uses regularly available statistics on import, industrial production and export of batteries and battery-containing electric and electronic equipment (EEE). To promote method use by other scholars with no access to such data, several empirically results and their trends over time, for different types of batteries occurrence among the EEE types are provided. The information provided by the method can be used to: identify drivers of battery consumption; study the dynamic behavior of battery flows – due to technology development, policies, consumers behavior and infrastructures. The method is exemplified by the study of battery flows in Sweden for years 1996–2013. The batteries were accounted, both in units and weight, as primary and secondary batteries; loose and integrated; by electrochemical composition and share of battery use between different types of EEE. Results show that, despite a fivefold increase in the consumption of rechargeable batteries, they account for only about 14% of total use of portable batteries. Recent increase in digital convergence has resulted in a sharp decline in the consumption of primary batteries, which has now stabilized at a fairly low level. Conversely, the consumption of integrated batteries has increased sharply. In 2013, 61% of the total weight of batteries sold in Sweden was collected, and for the particular case of alkaline manganese dioxide batteries, the value achieved 74%.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Consumption-based greenhouse gas emissions accounting with capital stock change highlights dynamics of fast-developing countries

Traditional consumption-based greenhouse gas emissions accounting attributed the gap between consumption-based and production-based emissions to international trade. Yet few attempts have analyzed the temporal deviation between current emissions and future consumption, which can be explained through changes in capital stock. Here we develop a dynamic model to incorporate capital stock change in consumption-based accounting. The new model is applied using global data for 1995–2009. Our results show that global emissions embodied in consumption determined by the new model are smaller than those obtained from the traditional model. The emissions embodied in global capital stock increased steadily during the period. However, capital plays very different roles in shaping consumption-based emissions for economies with different development characteristics. As a result, the dynamic model yields similar consumption-based emissions estimation for many developed countries comparing with the traditional model, but it highlights the dynamics of fast-developing countries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Research and Development Opportunities for Technologies to Influence Water Consumption Behavior

In April 2015, Argonne National Laboratory hosted a two-day workshop that convened water experts and stakeholders from across industry, government, and academia to undertake three primary tasks: 1) identify technology characteristics that are favorable for motivating behavioral change, 2) identify barriers that have prevented the development and market adoption of technologies with these characteristics in the water sector, and 3) identify concrete research and development pathways that could be undertaken to overcome these barriers, increase the penetration of technologies that influence water consumption behavior, and ultimately reduce domestic water consumption. While efforts to reduce water consumption have gained momentum in recent years, there are a number of key barriers that have limited the effectiveness of such efforts. Chief among these is the fact that many consumers have limited awareness of their water consumption patterns because of poor data availability, and/or are unmotivated to reduce their consumption because of low costs and split incentives. Without improved data availability and stronger price signals, it will be difficult to effect true transformative behavioral change. This report also reviews a number of technology characteristics that have successfully motivated behavioral change in other sectors, as well as several technologies that could be developed specifically for the water sector. Workshop participants discussed how technologies that provide active feedback and promote measurable goals and social accountability have successfully influenced changes in other types of behavior. A range of regulatory and policy actions that could be implemented to support such efforts are also presented. These include institutional aggregation, revenue decoupling, and price structure reforms. Finally, several R&D pathways were proposed, including efforts to identify optimal communication strategies and to better understand consumer perceptions and psychology as they relate to human behavior regarding water consumption. The findings presented here can help to inform policy makers as they develop new policies and seek to support new research to help consumers use water more efficiently. It is our hope that these findings will also be utilized to prioritize topics for additional follow-up workshops to address individual issues and barriers more directly and in more detail. The goal of such future workshops will be to develop specific solutions, research plans, and technology development pathways that can be undertaken to increase the market penetration of technologies that effect behavioral change and reduce water consumption.

42 ENGINEERING↗
DOE OSTI2025

An Advanced Microscopic Energy Consumption Model for Automated Vehicle:Development, Calibration, Verification

The automated vehicle (AV) equipped with the Adaptive Cruise Control (ACC) system is expected to reduce the fuel consumption for the intelligent transportation system. This paper presents the Advanced ACC-Micro (AA-Micro) model, a new energy consumption model based on micro trajectory data, calibrated and verified by empirical data. Utilizing a commercial AV equipped with the ACC system as the test platform, experiments were conducted at the Columbus 151 Speedway, capturing data from multiple ACC and Human-Driven (HV) test runs. The calibrated AA-Micro model integrates features from traditional energy consumption models and demonstrates superior goodness of fit, achieving an impressive 90% accuracy in predicting ACC system energy consumption without overfitting. A comprehensive statistical evaluation of the AA-Micro model's applicability and adaptability in predicting energy consumption and vehicle trajectories indicated strong model consistency and reliability for ACC vehicles, evidenced by minimal variance in RMSE values and uniform RSS distributions. Conversely, significant discrepancies were observed when applying the model to HV data, underscoring the necessity for specialized models to accurately predict energy consumption for HV and ACC systems, potentially due to their distinct energy consumption characteristics.

Ma, Ke↗