Search NASA⌕ Search

SEARCH · Search NASA

Results for “curb use”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Adaptive changes in sexual behavior in the high–risk population in response to human monkeypox transmission in Canada can help control the outbreak: Insights from a two–group, two–route epidemic model

Monkeypox, a zoonotic disease, is emerging as a potential sexually transmitted infection/disease, with underlying transmission mechanisms still unclear. We devised a risk-structured, compartmental model, incorporating sexual behavior dynamics. We compared different strategies targeting the high-risk population: a scenario of control policies geared toward the use of condoms and/or sexual abstinence (robust control strategy) with risk compensation behavior change, and a scenario of control strategies with behavior change in response to the doubling rate (adaptive control strategy). Monkeypox's basic reproduction number is 1.464, 0.0066, and 1.461 in the high-risk, low-risk, and total populations, respectively, with the high-risk group being the major driver of monkeypox spread. Policies imposing condom use or sexual abstinence need to achieve a 35% minimum compliance rate to stop further transmission, while a combination of both can curb the spread with 10% compliance to abstinence and 25% to condom use. With risk compensation, the only option is to impose sexual abstinence by at least 35%. Adaptive control is more effective than robust control where the daily sexual contact number is reduced proportionally and remains constant thereafter, shortening the time to epidemic peak, lowering its size, facilitating disease attenuation, and playing a key role in controlling the current outbreak.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

DEMONSTRATION OF A PASSIVE CONDENSER LOOP

Building HVAC consumes significant amount of energy. It is estimated that about 7% of the total electricity consumed by water cooled chiller is used to drive the condenser water pump. A passive condenser loop is developed to curb this energy consumption by replacing the open pumped loop to a closed loop thermosyphon system. The loop thermosyphon uses waste heat to circulate the condenser fluid, eliminating the electrical pumping power requirement and the large circulation pump. Since it is a closed loop, it also reduces the maintenance cost and enables both wet and dry cooling modes. A demonstration unit with a riser about 40 feet (12.2 meters) tall is fabricated and tested at powers up to 25 kW. The result has successfully showed that the loop thermosyphon is able to transfer the heat near isothermally (∆T < 0.4C) over the long distance without the need of any pump and consuming any electricity.

Loop thermosyphon, building HVAC, condenser loop↗
DOE OSTI2023

Drones, Delivery Robots, Driverless Cars, and Intelligent Curbs for Increasing Energy Productivity of First/Last Mile Goods Movement

The objective of the project is to use empirical testing, life cycle assessment, and systems analysis to research and demonstrate energy improvement when using goods delivery drones, eVTOL, ground delivery robots and automated vehicles compared to a baseline network. The research will also develop proof-of-concept testing, a model, and simulation for a smart curb space as an intelligently-managed urban delivery zone demonstrating additional improvement in energy productivity.

Scherer, Sebastian↗
DOE OSTI2024

Soil microbiome interventions for carbon sequestration and climate mitigation

Mitigating climate change in soil ecosystems involves complex plant and microbial processes regulating carbon pools and flows. Here, we advocate for the use of soil microbiome interventions to help increase soil carbon stocks and curb greenhouse gas emissions from managed soils. Direct interventions include the introduction of microbial strains, consortia, phage, and soil transplants, whereas indirect interventions include managing soil conditions or additives to modulate community composition or its activities. Approaches to increase soil carbon stocks using microbially catalyzed processes include increasing carbon inputs from plants, promoting soil organic matter (SOM) formation, and reducing SOM turnover and production of diverse greenhouse gases. Marginal or degraded soils may provide the greatest opportunities for enhancing global soil carbon stocks. Among the many knowledge gaps in this field, crucial gaps include the processes influencing the transformation of plant-derived soil carbon inputs into SOM and the identity of the microbes and microbial activities impacting this transformation. As a critical step forward, we encourage broadening the current widespread screening of potentially beneficial soil microorganisms to encompass functions relevant to stimulating soil carbon stocks. Moreover, in developing these interventions, we must consider the potential ecological ramifications and uncertainties, such as incurred by the widespread introduction of homogenous inoculants and consortia, and the need for site-specificity given the extreme variation among soil habitats. Incentivization and implementation at large spatial scales could effectively harness increases in soil carbon stocks, helping to mitigate the impacts of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Estimating Total Methane Emissions from the Denver-Julesburg Basin Using Bottom-Up Approaches

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.

03 NATURAL GAS↗
DOE OSTI2021

The role of current and emerging technologies in meeting Japan’s mid- to long-term carbon reduction goals

Using Japan as a proxy for a developed nation, we investigated the role of existing and nascent technologies in curbing carbon emissions. We simulated possible pathways to meeting 2030 and 2050 emission targets within the Japanese electricity supply sector using a single-region model in The Integrated MARKAL-EFOM System (TIMES). Critically, our simulations incorporate novel technologies like hydrogen electrolysers, carbon capture, photochemical water splitting, and emerging photovoltaic cells, assess long-term impacts up to the year 2100, and include life-cycle emissions and learning curves for parameters such as investment cost, efficiency, and emission coefficients. Results indicate that a hybrid approach, using nuclear power and hydrogen from renewable energy-based electrolysis, is cost-effective and provides long-term emission reduction along with energy security. Finally, nuclear, wind, solar, and hydrogen from renewables emerge as key emission reduction technologies, while natural gas with carbon capture plays a minor role in achieving emission reduction targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

The influence of tillage and fertilizer on the flux and source of nitrous oxide with reference to atmospheric variation using laser spectroscopy

Nitrous oxide (N 2 O) is the third most important long-lived greenhouse gas and agriculture is the largest source of N 2 O emissions. Curbing N 2 O emissions requires understanding influences on the flux and sources of N 2 O. We measured flux and evaluated microbial sources of N 2 O using site preference ( S P ; the intramolecular distribution of 15 N in N 2 O) in flux chambers from a grassland tilling and agricultural fertilization experiments and atmosphere. We identified values greater than that of the average atmosphere to reflect nitrification and/or fungal denitrification and those lower than atmosphere as increased denitrification. Our spectroscopic approach was based on an extensive calibration with 18 standards that yielded S P accuracy and reproducibility of 0.7 ‰ and 1.0 ‰, respectively, without preconcentration. Chamber samples from the tilling experiment taken ~ monthly over a year showed a wide range in N 2 O flux (0–1.9 g N 2 O-N ha -1 d -1 ) and S P (- 1.8 to 25.1 ‰). Flux and S P were not influenced by tilling but responded to sampling date. Large fluxes occurred in October and May in no-till when soils were warm and moist and during a spring thaw, an event likely representing release of N 2 O accumulated under snow cover. These high fluxes could not be ascribed to a single microbial process as S P differed among chambers. However, the year-long S P and flux data for no-till showed a slight direct relationship suggesting that nitrification increased with flux. The comparative data in till showed an inverse relationship indicating that high flux events are driven by denitrification. Corn ( Zea mays ) showed high fluxes and S P values indicative of nitrification ~ 4 wk after fertilization with subsequent declines in S P indicating denitrification. Although there was no effect of fertilizer treatment on flux or S P in switchgrass ( Panicum virgatum) , high fluxes occurred ~1 month after fertilization. In both treatments, S P was indicative of denitrification in many instances, but evidence of nitrification/fungal denitrification also prevailed. At 2 m atmospheric N 2 O S P had a range of 31.1 ‰ and 14.6 ‰ in the grassland tilling and agricultural fertilization experiments, respectively. These data suggest the influence of soil microbial processes on atmospheric N 2 O and argue against the use of the global average atmospheric S P in isotopic modeling approaches.

Environmental Sciences & Ecology↗
DOE OSTI2023

Curb Allocation and Pick-Up Drop-Off Aggregation for a Shared Autonomous Vehicle Fleet

Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and drop-off (PUDO) points for SAVs, much like bus stops, can be key in planning SAV fleet operations, since PUDOs impact SAV demand, route choices, passenger wait times, and network congestion. Unlike traditional human-driven taxis and ride-hailing vehicles like Lyft and Uber, SAVs are unlikely to engage in quasi-legal procedures, like double parking or fire hydrant pick-ups. In congested settings, like central business districts (CBD) or airport curbs, SAVs and others will not be allowed to pick up and drop off passengers wherever they like. This paper uses an agent-based simulation to model the impact of different PUDO locations and densities in the Austin, Texas CBD, where land values are highest and curb spaces are coveted. In this paper 18 scenarios were tested, varying PUDO density, fleet size and fare price. The results show that for a given fare price and fleet size, PUDO spacing (e.g., one block vs. three blocks) has significant impact on ridership, vehicle-miles travelled, vehicle occupancy, and revenue. A good fleet size to serve the region’s 80 core square miles is 4000 SAVs, charging a $1 fare per mile of travel distance, and with PUDOs spaced three blocks of distance apart from each other in the CBD.

Hunter, Christian B.↗
DOE OSTI2022

Technology Integration to Gain Commercial Efficiency for the Urban Goods Delivery System, Meet Future Demand for City Passenger and Delivery Load/Unload Spaces, and Reduce Energy Consumption

This three-year project supported by the U.S. Department of Energy Vehicle Technologies Office has the potential to radically improve the urban freight system in ways that help both the public and private sectors. Working from 2018-2021, project researchers at the University of Washington’s Urban Freight Lab and collaborators at the Pacific Northwest National Laboratory have produced key data, tested technologies in complex urban settings, developed a prototype parking availability app, and helped close major knowledge gaps. All the fruits of this project can be harnessed to help cities better understand, support and actively manage truck load/unload operations and their urban freight transport infrastructure. Project learnings and tools can be used to help make goods delivery firms more efficient by reducing miles traveled and the time it takes to complete deliveries, benefitting businesses and residents who rely on the urban freight system for supplies of goods. And, ultimately, these project learnings and tools can be used to make cities more livable by minimizing wasted travel, which, in turn, contributes to reductions in fuel consumption and emissions. Cities today are challenged to effectively and efficiently manage their infrastructure to absorb the impacts of ever-increasing e-commerce-fueled delivery demand. All delivery trucks need to park somewhere to unload and load. Yet today’s delivery drivers have no visibility on available parking until they arrive at a site, which may be full. That means they can wind up cruising for parking, which wastes time and fuel and contributes to congestion. Once drivers do find parking, the faster they can unload at the spot, the faster they free up space for other drivers, helping others avoid circling for parking. This makes the parking space—and thus the greater load/unload network—more productive. To this end, the research team successfully met the project’s three goals, developing and piloting strategies and technologies to: 1. Reduce parking-seeking behavior in the study area by 20%; 2. Reduce parcel truck dwell time (the time a truck spends in a spot to load/unload) in the study area by 30%; 3. Increase curb space, alley space and private loading bay occupancy rates in the study area. The research team met these goals by creating and piloting on Seattle streets OpenPark, a first-of-its-kind real-time and forecasting curb parking app customized for commercial delivery drivers—giving drivers the “missing link” in their commonly used routing tools that tell them how best to get to delivery locations, but not what parking is available to use when they get there. Installing in-ground sensors on commercial vehicle load zones (CVLZs) and passenger load zones (PLZs) in the 10-block study area in Seattle’s downtown neighbourhood of Belltown let researchers glean real-time curb parking data. The research team also met project goals by piloting three parcel lockers in public and private spaces open to any delivery carrier, creating a consolidated delivery hub that lets drivers complete deliveries faster and spend less time parked. Researchers collected and analysed data to produce the first empirical, robust, statistically significant results as to the impact of the lockers, and app, on on-the-ground operations. In addition to collecting and analyzing sensor and other real-time and historical data, researchers rode along with delivery drivers to confirm real-world routing and parking behavior. Researchers also surveyed building managers on their private loading bay operations to understand how to boost usage.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Airport Infrastructure Planning Using Multi-Stage Stochastic Programming

The Athena project, funded by the Department of Energy, has worked to identify the critical infrastructure at Dallas Fort Worth (DFW) Airport which influences mobility between the airport and the surrounding city of Dallas. Using scalable methods that can leverage HPC resources we have developed a multi-stage stochastic infrastructure expansion model for determining parking and curb modifications to the DFW Airport over a 20-year horizon. Additionally, we have explored the impacts of congestion pricing in conjunction with infrastructure modifications. Our multi-stage stochastic model is implemented using the mpi-sppy software and solved in parallel using progressive hedging on the National Renewable Energy Laboratory's HPC system Eagle. In this talk we present results from solving this model at scale.

airport planning↗
NASA NTRS2005

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Goetz, Scott J.↗
DOE OSTI2022

COVID-19 impacts on residential occupancy schedules and activities in U.S. Homes in 2020 using ATUS

Many aspects of the daily lives of those living in the United States were substantially impacted by the COVID-19 pandemic in the year 2020. A broad diversity of measures was implemented to curb the spread of the virus, many of which included adjustments to where and how people worked, went to school, and otherwise conducted their daily lives compared to pre-pandemic times. This has impacted how residential buildings are used, how much time people spend in their homes, and as a result, how much energy these buildings consume. The main objective of this study is to analyze, at a national scale, the differences in the occupancy schedules and activities conducted in homes in the U.S., as compared to pre-pandemic. 15 years of American Time Use Survey and Current Population Survey data, from 2006 to 2020, was used in this study to analyze the occupancy schedules for both pandemic (2020) and pre-pandemic (2006–2019) times. These impacts were also analyzed with respect to variables including, weekday/weekend, month of the year, age of the occupants, household income, and household size. The impact of the pandemic on occupant schedules were most substantial in the initial months, whereas as the months progressed, these occupancy profiles slowly changed. Across 2020, people spent, on average, 8 % more time (1.9 h) in their home on weekdays, and 3–6 % (1.2 h) on weekend days. The percentage of time spent for different activities and locations within homes were also studied. For 1-member households, their time spent at home decreased whereas for 2-, 3-, and 4- member households, they spent more time at home. Overall, people spent around 45% more time doing office- and work-related activities at home compared to pre-pandemic, which is likely due to increased remote working and schooling. This research helps to improve the understanding of the occupancy presence and absence profiles in U.S. residential buildings due to the pandemic and provides new insights as to modified profiles for researchers, building designers, and policy makers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Certified Green Building Materials: Policy Impact Assessment

Chinese building construction is rapidly expanding, making it critical to focus on energy efficiency to curb the increase of energy consumption and emissions over a building’s lifetime. A key mechanism to do so is through building material certification systems and programs. These establish how building materials will perform and can be used to promote energy and resource efficiency, which help create a more sustainable and healthy building industry. This report begins by identifying characteristics of a strong certification system and ways to improve existing systems. To curb building energy demand, the Chinese government began developing a building material certification program to encourage energy and resource efficiency in the building sector. A timeline is provided of their program’s development and provides analysis. China’s building material database is highlighted and analyzed for their significance and opportunities for improvement. The report then continues to analyze the importance of policies such as procurement programs, and the Chinese government is developing their procurement programs for certified green building materials. To understand the potential large-scale impacts of green building material certifications, we conducted an analysis of the environmental and market impact of a nationwide green building procurement policy for all new residential and commercial construction.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2012

Alternate-Fueled Combustion-Sector Emissions

In order to meet rapidly growing demand for fuel, as well as address environmental concerns, the aviation industry has been testing alternate fuels for performance and technical usability in commercial and military aircraft. Currently, alternate aviation fuels must satisfy MIL-DTL- 83133F(2008) (military) or ASTM D 7566- Annex(2011) (commercial) standards and are termed drop-in fuel replacements. Fuel blends of up to 50% alternative fuel blended with petroleum (JP-8), which have become a practical alternative, are individually certified on the market. In order to make alternate fuels (and blends) a viable option for aviation, the fuel must be able to perform at a similar or higher level than traditional petroleum fuel. They also attempt to curb harmful emissions, and therefore a truly effective alternate fuel would emit at or under the level of currently used fuel. This paper analyzes data from gaseous and particulate emissions of an aircraft combustor sector. The data were evaluated at various inlet conditions, including variation in pressure and temperature, fuel-to-air ratios, and percent composition of alternate fuel. Traditional JP-8+100 data were taken as a baseline, and blends of JP- 8+100 with synthetic-paraffinic-kerosene (SPK) fuel (Fischer-Tropsch (FT)) were used for comparison. Gaseous and particulate emissions, as well as flame luminosity, were assessed for differences between FT composition of 0%, 50%, and 100%. The data showed that SPK fuel (a FT-derived fuel) had slightly lower harmful gaseous emissions, and smoke number information corroborated the hypothesis that SPK-FT fuels are cleaner burning fuels.

Saxena, Nikita T.↗
NASA NTRS2013

Alternate-Fueled Combustor-Sector Emissions

In order to meet rapidly growing demand for fuel, as well as address environmental concerns, the aviation industry has been testing alternate fuels for performance and technical usability in commercial and military aircraft. In order to make alternate fuels (and blends) a viable option for aviation, the fuel must be able to perform at a similar or higher level than traditional petroleum fuel. They also attempt to curb harmful emissions, and therefore a truly effective alternate fuel would emit at or under the level of currently used fuel. This report analyzes data from gaseous and particulate emissions of an aircraft combustor sector. The data were evaluated at various inlet conditions, including variation in pressure and temperature, fuel-to-air ratios, and percent composition of alternate fuel. Traditional JP-8+100 data were taken as a baseline, and blends of JP-8+100 with synthetic-paraffinic-kerosene (SPK) fuel (Fischer-Tropsch (FT)) were used for comparison. Gaseous and particulate emissions, as well as flame luminosity, were assessed for differences between FT composition of 0, 50, and 100 percent. The data show that SPK fuel (an FT-derived fuel) had slightly lower harmful gaseous emissions, and smoke number information corroborated the hypothesis that SPK-FT fuels are cleaner burning fuels.

Saxena, Nikita T.↗
NASA NTRS2019

Success of Montreal Protocol Demonstrated by Comparing High-Quality UV Measurements with “World Avoided” Calculations from Two Chemistry-Climate Models

The Montreal protocol on Substances that Deplete the ozone Layer has been hailed as the most successful environmental treaty ever (https://www.unenvironment.org/news-and-stories/story/montreal-protocol-triumph-treaty). Yet, although our main concern about ozone depletion is the subsequent increase in harmful solar UV radiation at the earth’s surface, no studies to date have demonstrated its effectiveness in that regard. Here we use long-term UV Index (UVI) data derived from high-quality UV spectroradiometer measurements to demonstrate its success in curbing increases in UV radiation. Without this landmark agreement, UVi values would have increased at mid-latitude locations by approximately 20% between the early 1990s and today and would approximately quadruple at mid-latitudes by 2100. In contrast, an analysis of UVI data from multiple clean-air sites shows that maximum daily UVI values have remained essentially constant over the last ~20 years in all seasons, and may even have decreased slightly in the southern hemisphere, especially in Antarctica, where effects of ozone depletion were larger. Reconstructions of the UVi from total ozone data show evidence of increasing UVI levels in the 1980s, but unfortunately, there are no high-quality UV measurements available prior to the early 1990s to confirm these increases with direct observations.

UV Index (UVI) data derived from high-quality UV s↗
DOE OSTI2020

Smart Planning Support for Nuclear Power Plant Work Planners

Operation and Maintenance costs of a nuclear power plant account for 60% of overall plant costs due to the nuclear industry?s risk-adverse culture (World Nuclear Association, 2020). The industry relies on highly conservative estimates to avoid risk and brute force reactions to manage the unexpected and keep a plant running safely. This approach has kept plants operating safer than any other power source available over the last six decades (Ritchie, 2020). However, these conservative methods have cost the nuclear industry in market competitiveness. The solution? Transform the conservative approaches to accurate, efficient, and still safe data-driven approaches that leverage advanced technologies available in the digital age of operation. This project endeavored to identify two key aspects to successfully incorporate historical work execution data. First, where in the work management process is that information most pertinent? Next, what variables are key to informing the best strategy for organizing the upcoming work? The Smart Planner uses data collected by dynamic work instructions to provide a basis for suggesting requirements of similar, upcoming work packages. Further, it curbs inefficiencies of the work management process by analyzing the likelihood of discovery work, offering suggestions to build a contingency package. All this taking place as the work planner builds work packages that meet the predetermined scope of work to be performed.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Computational Analysis of Water Film Thickness During Rain Events for Assessing Hydroplaning Risk Part 2: Rough Road Surfaces

Hydroplaning occurs when a water film forms on a road during a rain event and vehicles are traveling at a speed that does not provide sufficient time for the tires to push the water film out of the tire path. Under these conditions, the tire loses contact with the road and the driver may lose control over the vehicle. The present study is a part of a multiyear research effort aimed at gaining a better understanding of the factors that contribute to hydroplaning risk in order to minimize the occurrence of hydroplaning accidents. Three-dimensional computational fluid dynamics (CFD) analysis was used to investigate the water film thickness on multilane roads, one of the key parameters in evaluating hydroplaning risk. In the first part of the study, water films forming on wide roadways, i.e. multilane highways with 2, 4, and 6 lanes per side, were analyzed, with varying cross slope, longitudinal slope, and rainfall rate. Roadways with and without curbs and drainage were included in the analysis. The analysis in the first part was limited to nearly smooth asphalt or concrete surfaces because the maximum roughness height that can be specified in a CFD model using wall functions to determine shear stress at the road surface boundary is one half the thickness of computational cell layer adjacent to the boundary and the need to resolve the vertical velocity distribution in a thin water film requires cell layers that are a fraction of a millimeter thick. In this part of the study, the analysis was extended to consider the influence of pavement roughness over a range extending up 3.6 mm on the development of water film thickness. Various methods of modeling roughness were investigated and are presented: the roughness height model, a meshed-out geometry of the macrotexture of the pavement, and a porous region model. The computational results were analyzed and compared with experimental measurements performed by Gallaway et al.

42 ENGINEERING↗