SEARCH · Engineering Papers

Results for “demand modelling”

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 109 records · Page 6

All sources NASA NTRS DOE OSTI

NASA NTRS1987

Approaches to the automatic generation and control of finite element meshes

The algorithmic approaches being taken to the development of finite element mesh generators capable of automatically discretizing general domains without the need for user intervention are discussed. It is demonstrated that because of the modeling demands placed on a automatic mesh generator, all the approaches taken to date produce unstructured meshes. Consideration is also given to both a priori and a posteriori mesh control devices for automatic mesh generators as well as their integration with geometric modeling and adaptive analysis procedures.

Shephard, Mark S.↗

DOE OSTI2025

National Modeling of Geothermal District Energy Systems with Ambient-Temperature Loops Using dGeo

Geothermal district energy systems (DES) with ambient-temperature loops, also known as thermal energy networks, are one option for decarbonizing space heating and cooling loads. Geothermal fifth-generation DES include an "ambient" temperature thermal loop that connects heat pumps at each building with thermal balancing sources such as geothermal borehole fields. Heating and cooling are provided via a water-source heat pump at each end-user. This project seeks to analyze the nationwide potential for ambient-temperature loop districts by creating a new module within the Distributed Geothermal Market Demand Model (dGeo). dGeo is an agent-based modeling tool for distributed geothermal resources; it can investigate potential on a nationwide or statewide scale using geospatial data for all 50 states and thermal demands for existing buildings. This process allows for high-level estimates of technical and economic potential for ambient-temperature loop districts across the United States. A lookup table was created using GHEDesigner to size borehole fields for different thermal loads and ground conditions experienced across the country. A cost and financing structure, along with incentives, were applied. Cost estimates include costs for the distribution network, borehole field installation and operation, and circulation pump operation, while savings are calculated based on energy bills for building owners (agents). This newly developed module can be used for assessing which areas of the country have the highest potential for agent benefits from ambient-temperature loop installation and assess the impact of future cost and price scenarios. Initial results for statewide analysis (for Vermont) and nationwide (for United States) are provided. Future work includes expanding the module to consider mixed residential and commercial districts as well as evaluating multiple cost scenarios.

ambient-temperature loop↗

DOE OSTI2024

National Modeling of Geothermal District Energy Systems with Ambient-Temperature Loops Using dGeo: Preprint

Geothermal district energy systems (DES) with ambient-temperature loops, also known as thermal energy networks, are one option for decarbonizing space heating and cooling loads. Geothermal fifth-generation DES include an "ambient" temperature thermal loop that connects heat pumps at each building with thermal balancing sources such as geothermal borehole fields. Heating and cooling are provided via a water-source heat pump at each end-user. This project seeks to analyze the nationwide potential for ambient-temperature loop districts by creating a new module within the Distributed Geothermal Market Demand Model (dGeo). dGeo is an agent-based modeling tool for distributed geothermal resources; it can investigate potential on a nationwide or statewide scale using geospatial data for all 50 states and thermal demands for existing buildings. This process allows for high-level estimates of technical and economic potential for ambient-temperature loop districts across the United States. Using GHEDesigner, a lookup table was created to size borehole fields for different thermal loads and ground conditions experienced across the country. A cost and financing structure, along with incentives, were applied. Cost estimates include costs for the distribution network, borehole field installation and operation, and circulation pump operation, while savings are calculated based on agent energy bills. This newly developed module can be used for assessing which areas of the country have the highest potential for agent benefits from ambient-temperature loop installation and assess the impact of different costing and pricing future scenarios. While the code is still under development and nationwide simulations are ongoing, initial results for two states are provided. Future work includes expanding the module to consider mixed residential and commercial districts and considering multiple costing scenarios.

ambient temperature loop↗

NASA NTRS2004

Simulation of Aerosols and Chemistry with a Unified Global Model

This project is to continue the development of the global simulation capabilities of tropospheric and stratospheric chemistry and aerosols in a unified global model. This is a part of our overall investigation of aerosol-chemistry-climate interaction. In the past year, we have enabled the tropospheric chemistry simulations based on the GEOS-CHEM model, and added stratospheric chemical reactions into the GEOS-CHEM such that a globally unified troposphere-stratosphere chemistry and transport can be simulated consistently without any simplifications. The tropospheric chemical mechanism in the GEOS-CHEM includes 80 species and 150 reactions. 24 tracers are transported, including O3, NOx, total nitrogen (NOy), H2O2, CO, and several types of hydrocarbon. The chemical solver used in the GEOS-CHEM model is a highly accurate sparse-matrix vectorized Gear solver (SMVGEAR). The stratospheric chemical mechanism includes an additional approximately 100 reactions and photolysis processes. Because of the large number of total chemical reactions and photolysis processes and very different photochemical regimes involved in the unified simulation, the model demands significant computer resources that are currently not practical. Therefore, several improvements will be taken, such as massive parallelization, code optimization, or selecting a faster solver. We have also continued aerosol simulation (including sulfate, dust, black carbon, organic carbon, and sea-salt) in the global model to cover most of year 2002. These results have been made available to many groups worldwide and accessible from the website http://code916.gsfc.nasa.gov/People/Chin/aot.html.

Chin, Mian↗

DOE OSTI2024

Integrating the Mobility Energy Productivity Metric into the CDOT Statewide Model

The Mobility Energy Productivity (MEP) metric measures the quality of mobility at a specific location and can be used to evaluate how changes to transportation systems impact the mobility of that location over time, such as through infrastructure investments. The objective of this study is to demonstrate integration of the MEP metric into CDOT's transportation planning process by leveraging data from their statewide travel demand model. We evaluate the MEP metric in 2015 as well as 2030 baselines and projected impacts in 2030 for two different regions in Colorado under multiple scenarios across multiple modes (driving, walking, biking, and transit). It was found that increasing development (increasing population density, jobs, and opportunities) had a significant impact on MEP, independent of any specific alternatives. For drive mode, there was a trade- off of increasing congestion on the road network and increasing job and opportunity access. Impacts to bike, walk, and transit MEP were also demonstrated in both regions. This report shows how MEP can be used as a tool to support evaluating the impacts of various transportation projects across the state. With projections of significant growth across the state of Colorado, access to the increasing opportunities and jobs will be important to understand through the context of energy efficiency. MEP could support future project evaluation and decision-making by enabling the unique and important dimension of energy- efficient accessibility of a transportation system.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Parking Strategies and Outcomes for Shared Autonomous Vehicle Fleet Operations

Parking spots are a premium commodity, especially in dense downtown settings, so this study examines the service impacts of shared autonomous vehicles (SAVs) parking in legal on- or off-street locations when idle across Travis County in Austin, Texas. Here, using an agent-based activity-based travel demand model with dynamic traffic simulation, two restricted-parking strategies for SAVs were simulated. SAVs either found the nearest available parking spot or the lowest-cost spot (via a tradeoff of parking fees and distance-based costs). Two comparisons were conducted to analyze the impacts of these strategies. First, two restricted parking strategies were compared, where SAVs park without competition with private human-driven vehicles (HVs) for parking locations. Second, a more realistic analysis compared two SAV parking strategies with a scenario where SAVs remain idle in place. Private HVs in all scenarios and strategies of this comparison park at the closest designated location unless they opt for private parking. Using a supply of 8,400 aggregated parking locations in Austin, this study simulated fleet performance under different trip demands, with SAV fares of $\$0.62$ per kilometer ($\$1$ per mile) plus a $\$1$ fixed pickup fee with dynamic ridesharing permitted. Parking costs were negligible in both SAV parking search strategies applied to the Austin network because of the region’s provision of mostly free parking. Requiring SAVs to park on designated on- and off-street parking locations and parking lots (restricted parking) also increased parking costs for HV drivers by up to 22% since SAVs occupied some free parking spaces, especially in the least-cost parking search strategy.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Multiscale and multidimensional modeling of particle acceleration and transport in solar flares

Multi-messenger, multi-viewpoint, and time-resolved observations of solar flares are now providing unprecedented constraints on particle acceleration sites, energy conversion, and energy transport. The interpretation of current observations, including microwave imaging spectroscopy from EOVSA, hard x-ray (HXR) imaging from Solar Orbiter/STIX, gamma-ray diagnostics from Fermi, and in situ measurements from Parker Solar Probe and Solar Orbiter, collectively demands modeling frameworks that go beyond traditional spatially unresolved, one-zone models or single-mechanism descriptions. This review surveys multiscale and multidimensional modeling approaches, including kinetic, magnetohydrodynamic (MHD), and macroscopic particle models, that are being developed to meet the need. Kinetic simulations reveal that three-dimensional (3D) effects, including field-line chaos and self-generated turbulence, are essential for sustained power-law particle acceleration. MHD simulations now capture flux-rope eruptions, plasmoid-unstable current sheets, and turbulent flare regions in realistic magnetic topologies. Macroscopic models coupling MHD with energetic-particle models produce spatially resolved electron distributions and synthetic HXR and microwave emissions for direct comparison with observations. Despite these advances, outstanding challenges remain in bridging kinetic and global scales, improving MHD simulations and macroscopic particle models, and achieving quantitative model-observation closure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Propagating synthetic populations with dynamic Bayesian networks: a framework for long-horizon demographic forecasting

This study presents a dynamic demographic microsimulator using dynamic Bayesian networks to forecast long–term changes in household and individual life events. Leveraging longitudinal Panel Study of Income Dynamics (PSID) data, two networks for individuals and households were modeled to simulate transitions in employment, income, education, marriage, childbirth, leaving the parental home, home ownership, mortality, and household formation or dissolution. Across 1,000 simulation runs spanning 24 years, household–level outcomes remain highly accurate and individual–level predictions reasonable. Although accuracy naturally declines with projection horizon, performance remains promising at both levels. This study addresses a key limitation of existing population synthesis models, which typically generate only a single static snapshot of the population. In conclusion, by introducing a framework that propagates cross-sectional outputs into the future, the microsimulator enables the tracking of demographic evolution over time, enhances realism in population-based simulations, and supplies credible inputs to agent-based travel demand models.

Demographic modeling↗

NASA NTRS2015

Holiday in Lights: Tracking Cultural Patterns in Demand for Energy Services

Successful climate change mitigation will involve not only technological innovation, but also innovation in how we understand the societal and individual behaviors that shape the demand for energy services. Traditionally, individual energy behaviors have been described as a function of utility optimization and behavioral economics, with price restructuring as the dominant policy lever. Previous research at the macro-level has identified economic activity, power generation and technology, and economic role as significant factors that shape energy use. However, most demand models lack basic contextual information on how dominant social phenomenon, the changing demographics of cities, and the sociocultural setting within which people operate, affect energy decisions and use patterns. Here we use high-quality Suomi-NPP VIIRS nighttime environmental products to: (1) observe aggregate human behavior through variations in energy service demand patterns during the Christmas and New Year's season and the Holy Month of Ramadan and (2) demonstrate that patterns in energy behaviors closely track sociocultural boundaries at the country, city, and district level. These findings indicate that energy decision making and demand is a sociocultural process as well as an economic process, often involving a combination of individual price-based incentives and societal-level factors. While nighttime satellite imagery has been used to map regional energy infrastructure distribution, tracking daily dynamic lighting demand at three major scales of urbanization is novel. This methodology can enrich research on the relative importance of drivers of energy demand and conservation behaviors at fine scales. Our initial results demonstrate the importance of seating energy demand frameworks in a social context.

VIIRS night sky↗

DOE OSTI2026

Transit Rider/Travel Behavior Inventory Survey - Minneapolis-St. Paul Metro - 2010

The Metropolitan Council administered a system-wide transit on-board survey between September and November 2010 as part of the 2010 Travel Behavior Inventory to provide detailed transit usage patterns and rider information to support modeling and planning efforts. The study’s focus was to capture only the most current and reliable data necessary to determine future public transportation needs in the Minneapolis region. The study was structured to collect detailed transit ridership data for different routes during different times of day to develop a disaggregate transit trip table that will support advanced travel demand modeling. The study was designed to leverage existing data sources, such as the 2005 on-board survey, to provide the best quality data to update the Travel Behavior Inventory in the Minneapolis-Saint Paul metropolitan area.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

PR100: Estimated Medium- and Heavy-Duty Electric Vehicle Adoption and Load Estimation in Puerto Rico through 2050

The 2-year Puerto Rico Grid Resilience and Transition to 100% Renewable Energy Study analyzed stakeholder-driven pathways to Puerto Rico’s clean energy future. Outputs relating to electricity demand modeling were partially informed by estimates of electric vehicle adoption across all classes of medium- and heavy-duty vehicles (MHDVs), and the ensuing charging loads. To create these estimates, the team developed a transportation model for MHDVs in Puerto Rico to estimate the amount and geospatial distribution of energy used. Charging schedules for the different end uses of MHDVs were then used to construct electric load shapes assuming a portion of those vehicles would be replaced by battery electric counterparts. Study results showed that, by 2050, electric vehicles may constitute roughly 50% of the MHDV population in Puerto Rico. The resulting electrical demand curve attributable to MHDV charging showed that, for solar energy-based electrical systems with limited energy storage, this demand may create challenges unless appropriately managed either on the demand or supply side.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

A rapid embodied carbon assessment tool for priority materials

Embodied carbon limits within building materials are a driving factor in global trade, generating new research and analysis tools in industry. These product assessments, which require utilizing life-cycle assessment (LCA) across broad supply chains, can be expensive, time and data-intensive, and subject to significant variations. Existing methods and tools, such as specific environmental product declarations, typically do not capture these variations and dynamics in supply and manufacturing. Moreover, models and tools must enable stakeholders to assess customized supply chains and future scenarios. In this study, we present the Rapid Embodied Carbon Assessment and Target-setting for Emissions-intensive Materials (REDuCE) tool for building materials. We developed a tool that allows users to select production technologies, transportation mode and distances, concrete carbonation, fuel sources, and regional electricity mixes to supply customization for cement and concrete produced and consumed in California. We generated and integrated a material demand model using residential building stock projections. We provide the user with a wide range of mitigation alternatives through low-carbon production pathways, material use efficiency, transportation modes, and projected electricity grid mixes. In a case study application through four mitigation scenarios, we find emission savings up to 80% by maximizing user mitigation alternatives, primarily driven by reductions in material use intensities. This work represents a foundation for expanding LCA and embodied carbon tools to better enable stakeholders to rapidly and accurately assess customized supply chains while meeting trade requirements.

building materials↗

DOE OSTI2021

Learning electric vehicle driver range anxiety with an initial state of charge-oriented gradient boosting approach

This manuscript focuses on the modeling of electric vehicle (EV) driver’s range anxiety, a fear that a vehicle does not have sufficient range, or state of charge (SOC) of the battery pack, to reach its destination and would strand its occupants. Despite numerous research studies on the modeling of charging behaviors, modeling efforts to understand at what battery percentages do EV drivers charge their vehicles, and what are the associated contributing factors, are rather limited. To this end, an ensemble learning model based on gradient boosting is developed. The model sequentially fits new predictors to new residuals of the previous prediction and, then, minimizes the loss when adding the latest prediction. A total of 18 features are defined and extracted from the multisource data, which cover information on driver, vehicles, stations, traffic conditions, as well as spatial-temporal context information of the charging events. The analyzed dataset includes 4.5-year’s charging event log data from 3,096 users and 468 public charging stations in Kansas City Missouri, and the macroscopic travel demand model maintained by the metropolitan planning organization. Here, the result shows the proposed model achieved a satisfactory result with a R square value of 0.54 and root mean square error of 0.14, both better than multiple linear regression model and random forest model. To reduce range anxiety, it is suggested that the priorities of deploying new charging facilities should be given to the areas with higher daily traffic prediction, with more conservative EV users or that are further from residential areas.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRSDate not supplied

Regional Modeling and Simulation for Vertiport Location Assessment

There is increasing interest in the Urban Air Mobility concept and the realization of electric Vertical Take-Off and Landing (e-VTOL) vehicles flying in the National Airspace System. NASA, FAA, and the industry are investigating various aspects of this new mode of transportation for cargo and humans. There are significant challenges in making this mode a reality, including feasibility, safety, infrastructure, traffic management, public acceptance, and scalability. From the infrastructure perspective, one of the aspects that needs to be addressed is the location of vertiports (named similar to heliports, for vertical take-off and landing vehicles). There is significant on-going research for selecting location of vertiports. However, the locations are largely based on demand models. Also, these efforts are focused in specific local regions, San Francisco/Bay Area, Chicago, Tampa, etc. This talk presents an approach to determine the location of vertiports in regional areas (across the United States), incorporating the desire to have certain attributes closer to or further from the location using a regional modeling tool. The feasibility of flying e-VTOL vehicles between various vertiport locations is also presented using a mobility operations simulation tool.

Air Mobility↗

DOE OSTI2026

Interaction between the emerging components of online shopping and in-person activities: insights from a behavioral survey

The rise of technological advancements has led to the commonplace practice of online shopping for retail, grocery, and food. However, little research has been conducted on the interplay of these components in burdened communities (BCs) that face issues of marginalization and limited access to digital resources. Here, this study aims to provide a comprehensive understanding of travel behavior changes by analyzing the interconnectedness of the emerging components of online shopping (retail, grocery, and food) and in-person activities in both BCs and non-BCs. A unique household-level database is created by linking the 2021 Puget Sound Household Travel Survey and the US Department of Transportation’s burdened community databases, and a conditional mixed process model is estimated to account for unobserved endogeneity. The findings suggest households living in BCs are less likely to order online retail goods and groceries compared to non-BC households. Additionally, the probability of making more restaurant trips decreases for households living in BCs. The study highlights the digital divide that exists in BCs and the differences in online and in-person shopping activities across socioeconomic levels. Policymakers may address these disparities to promote better access to goods and services for all. Besides, planners may need to improve the travel demand models by accounting for the emerging components of online shopping and the trip frequencies by purpose in BCs.

Digital Divide↗

NASA NTRS2006

Haughton-Mars Project Expedition 2005

The 2005 expedition to the Haughton-Mars Project (HMP) research station on Devon Island was part of a NASA-funded project on Space Logistics. A team of nine r&searchers from MIT went to the Canadian Arctic to participate in the annual I-IMP field campaign from July 8 to August 12, 2005. We investigated the applicability of the HMP research station as an analogue for planetary macro- and micro-logistics to the Moon and Mars, and began collecting data for modeling purposes. We also tested new technologies and procedures to enhance the ability of humans and robots to jointly explore remote environments. The expedition had four main objectives. We briefly summarize our key findings in each of these areas. 1. Classes of Supply: First, we wanted to understand what supply items existed at the HMP research station in support of planetary science and exploration research at and around the Haughton Crater. We also wanted to quantify the total amount of imported mass at HMP and compare this with predictions from existing parametric lunar base demand models. 2. Macro-Logistics Transportation Network: Our second objective was to understand the nodes, transportation routes, vehicles, capacities and crew and cargo mass flow rates required to support the HMP logistics network. 3. Agent and Asset Tracking: Since the current inventory management system on ISS relies heavily on barcodes and manual tracking, we wanted to test new automated technologies and procedures such as radio frequency identification RFID) to support exploration logistics. 4. Micro-Logistics (EVA): Finally, we wanted to understand the micro-logistical requirements of conducting both short (<1 day) and long traverses in the Mars-analog terrain on Devon Island. Micro-logistics involves the movement of surface vehicles, people and supplies from base to various exploration sites over short distances (<100 km).

deWeck, Olivier↗

DOE OSTI2024

GPS-supported smartphone app-based integrated travel diary and time-use data collection: challenges and lessons learned

Travel behaviour and time-use data are two vital data sources for travel demand modelling. Travel behaviour is traditionally collected through household travel surveys, enhanced by using GPS-supported smartphone apps for passive location data collection. However, recruiting individuals willing to install these apps with sustained motivation to continue participation has been a critical challenge. This paper shares insights from a travel and time-use data collection procedure in Chicago and Sydney using the Fourstep app. Social media platforms were utilised as a solution to recruit participants in Chicago, where an international market research company failed to accomplish the task. This paper also discusses the challenges we faced and suggests ways to overcome them, offering valuable guidance to researchers in recruiting participants for smartphone application-based data collection. It also offers an analysis of travel, time-use, and travel-based multitasking behaviours based on the data collected from the Chicago and Sydney samples.

GPS-supported smartphone apps↗

DOE OSTI2026

Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements

Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗