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At least 289 records · Page 16

Land use classification for hydrologic models using interactive machine classification of LANDSAT data

Models designed to simulate the hydrology of urban areas require input parameters describing the land use and degree of imperviousness of the watershed. Unfortunately, the magnitude and spatial distribution of these parameters are rather difficult to estimate when a large watershed is involved. Trade-offs between accuracy of the model parameters and the time or money available for their determination must be made. Because of the necessity of such trade-offs, a study was developed to investigate the use of computer aided analysis of LANDSAT multispectral data in estimating percent of imperviousness and associated land uses needed in urban hydrologic modeling. An interactive computer was used to delineate seven land use classifications in the 342 sq. km. Maryland portion of the Anacostia River Basin from LANDSAT data. These results compared favorably with those of an earlier study which obtained the same information through analysis of aerial photographs having a scale of 1:4800. Approximately 94 man days were required to complete the land use analysis using the aerial photographs while less than three man days were required to accomplish similar tasks using the LANDSAT data.

Thomas J. Jackson↗

A procedure used for a ground truth study of a land use map of North Alabama generated from LANDSAT data

A land use map of a five county area in North Alabama was generated from LANDSAT data using a supervised classification algorithm. There was good overall agreement between the land use designated and known conditions, but there were also obvious discrepancies. In ground checking the map, two types of errors were encountered - shift and misclassification - and a method was developed to eliminate or greatly reduce the errors. Randomly selected study areas containing 2,525 pixels were analyzed. Overall, 76.3 percent of the pixels were correctly classified. A contingency coefficient of correlation was calculated to be 0.7 which is significant at the alpha = 0.01 level. The land use maps generated by computers from LANDSAT data are useful for overall land use by regional agencies. However, care must be used when making detailed analysis of small areas. The procedure used for conducting the ground truth study together with data from representative study areas is presented.

Downs, S. W., Jr.↗

NASA Integrated Model Centric Architecture (NIMA) Model Use and Re-Use

This whitepaper accepts the goals, needs and objectives of NASA's Integrated Model-centric Architecture (NIMA); adds experience and expertise from the Constellation program as well as NASA's architecture development efforts; and provides suggested concepts, practices and norms that nurture and enable model use and re-use across programs, projects and other complex endeavors. Key components include the ability to effectively move relevant information through a large community, process patterns that support model reuse and the identification of the necessary meta-information (ex. history, credibility, and provenance) to safely use and re-use that information. In order to successfully Use and Re-Use Models and Simulations we must define and meet key organizational and structural needs: 1. We must understand and acknowledge all the roles and players involved from the initial need identification through to the final product, as well as how they change across the lifecycle. 2. We must create the necessary structural elements to store and share NIMA-enabled information throughout the Program or Project lifecycle. 3. We must create the necessary organizational processes to stand up and execute a NIMA-enabled Program or Project throughout its lifecycle. NASA must meet all three of these needs to successfully use and re-use models. The ability to Reuse Models a key component of NIMA and the capabilities inherent in NIMA are key to accomplishing NASA's space exploration goals. 11

Conroy, Mike↗

Using Remotely Sensed Data and Watershed and Hydrodynamic Models to Evaluate the Effects of Land Cover Land Use Change on Aquatic Ecosystems in Mobile Bay, AL

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land cover land use (LCLU) change in the two counties surrounding Mobile Bay (Mobile and Baldwin) on SAV stressors and controlling factors (temperature, salinity, and sediment) in the Mobile Bay estuary. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for LCLU scenarios in 1948, 1992, 2001, and 2030. Remotely sensed Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 LCLU scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the estuary. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid throughout Mobile Bay and adjacent estuaries. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to LCLU driven flow changes with the restoration potential of SAVs. Data products and results are being integrated into NOAA s EcoWatch and Gulf of Mexico Data Atlas online systems for dissemination to coastal resource managers and stakeholders. Objective 1: Develop and utilize Land Use scenarios for Mobile and Baldwin Counties, AL as input to models to predict the affects on water properties (temperature,salinity,)for Mobile Bay through 2030. Objective 2: Evaluate the impact of land use change on seagrasses and SAV in Mobile Bay. Hypothesis: Urbanization will significantly increase surface flows and impact salinity and temperature variables that effect seagrasses and SAVs.

Al-Hamdan, Mohammad↗

Preparation of a Bimetal Using Mechanical Alloying for Environmental or Industrial Use

Following the 1976 Toxic Substances Control Act ban on their manufacture, PCBs remain an environmental threat. PCBs are known to bio-accumulate and concentrate in fatty tissues. Further complications arise from the potential for contamination of commercial mixtures with other more toxic chlorinated compounds such as polychlorinated dibenzodioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). Until recently, only one option was available for the treatment of PCB-contaminated materials: incineration. This may prove to be more detrimental to the environment than the PCBs themselves due to the potential for formation of PCDDs. Metals have been used for the past ten years for the remediation of halogenated solvents and other contaminants in the environment; however, zero-valent metals alone do not possess the activity required to dehalogenate PCBs. Palladium has been shown to act as an excellent catalyst for the dechlorination of PCBs with active metals. This invention is a method for the production of a palladium/magnesium bimetal capable of dechlorinating PCBs using mechanical milling/mechanical alloying. Other base metals and catalysts may also be alloyed together (e.g., nickel or zinc) to create a similarly functioning catalyst system. Several bimetal catalyst systems currently can be used for processes such as hydrogen peroxide synthesis, oxidation of ethane, selective oxidation, hydrogenation, and production of syngas for further conversion to clean fuels. The processes for making these bimetal catalysts often involve vapor deposition. This technology provides an alternative to vapor deposition that may provide equally active catalysts. A hydrogenation catalyst including a base material coated with a catalytic metal is made using mechanical milling techniques. The hydrogenation catalysts are used as an excellent catalyst for the dehalogenation of contaminated compounds and the remediation of other industrial compounds. The mechanical milling technique is simpler and cheaper than previously used methods for producing hydrogenation catalysts. Preferably, the hydrogenation catalyst is a bimetallic particle formed from a zero-valent iron or zero-valent magnesium particle coated with palladium that is impregnated onto a high-surface-area graphite support. The zero-valent metal particles should be microscale or nanoscale zero-valent magnesium or zero-valent iron particles. Other zero-valent metal particles and combinations may be used. Additionally, the base material may be selected from a variety of minerals including, but not limited to, alumina and zeolites. The catalytic metal is preferably selected from the group consisting of noble metals and transition metals, preferably palladium. The mechanical milling process includes milling the base material with a catalytic metal impregnated into a high-surface-area support to form the hydrogenation catalyst. In a preferred mechanical milling process, a zero-valent metal particle is provided as the base material, preferably having a particle size of less than about 10 microns, preferably 0.1 to 10 microns or smaller, prior to milling. The catalytic metal is supported on a conductive carbon support structure prior to milling. For example, palladium may be impregnated on a graphite support. Other support structures such as semiconductive metal oxides may also be used.

Quinn, Jacqueline↗

Electrically Heated Testing of the Kilowatt Reactor Using Stirling Technology (KRUSTY) Experiment Using a Depleted Uranium Core

The Kilopower project aims to develop and demonstrate scalable fission-based power technology for systems capable of delivering 110 kW of electric power with a specific power ranging from 2.5 - 6.5 Wkg. This technology could enable high power science missions or could be used to provide surface power for manned missions to the Moon or Mars. NASA has partnered with the Department of Energys National Nuclear Security Administration, Los Alamos National Labs, and Y-12 National Security Complex to develop and test a prototypic reactor and power system using existing facilities and infrastructure. This technology demonstration, referred to as the Kilowatt Reactor Using Stirling TechnologY (KRUSTY), will undergo nuclear ground testing in the summer of 2017 at the Nevada Test Site. The 1 kWe variation of the Kilopower system was chosen for the KRUSTY demonstration. The concept for the 1 kWe flight system consist of a 4 kWt highly enriched Uranium-Molybdenum reactor operating at 800 degrees Celsius coupled to sodium heat pipes. The heat pipes deliver heat to the hot ends of eight 125 W Stirling convertors producing a net electrical output of 1 kW. Waste heat is rejected using titanium-water heat pipes coupled to carbon composite radiator panels. The KRUSTY test, based on this design, uses a prototypic highly enriched uranium-molybdenum core coupled to prototypic sodium heat pipes. The heat pipes transfer heat to two Advanced Stirling Convertors (ASC-E2s) and six thermal simulators, which simulate the thermal draw of full scale power conversion units. Thermal simulators and Stirling engines are gas cooled. The most recent project milestone was the completion of non-nuclear system level testing using an electrically heated depleted uranium (non-fissioning) reactor core simulator. System level testing at the Glenn Research Center (GRC) has validated performance predictions and has demonstrated system level operation and control in a test configuration that replicates the one to be used at the Device Assembly Facility (DAF) at the Nevada National Security Site. Fabrication, assembly, and testing of the depleted uranium core has allowed for higher fidelity system level testing at GRC, and has validated the fabrication methods to be used on the highly enriched uranium core that will supply heat for the DAF KRUSTY demonstration.

Briggs, Maxwell H.↗

Electrically Heated Testing of the Kilowatt Reactor Using Stirling TechnologY (KRUSTY) Experiment Using a Depleted Uranium Core

The Kilopower project aims to develop and demonstrate scalable fission-based power technology for systems capable of delivering 1 to 10 kW of electric power with a specific power ranging from 2.5 to 6.5 W/kg. This technology could enable high-power science missions or could be used to provide surface power for manned missions to the Moon or Mars. NASA has partnered with the U.S. Department of Energy's National Nuclear Security Administration, Los Alamos National Laboratory, Nevada National Security Site (NNSS), and Y−12 National Security Complex to develop and test a prototypic reactor and power system using existing facilities and infrastructure. This technology demonstration, referred to as the "Kilowatt Reactor Using Stirling TechnologY (KRUSTY)," will undergo nuclear ground testing by the end of calendar year (CY) 2017 at the NNSS. The 1-kWe variation of the Kilopower system was chosen for the KRUSTY demonstration. The concept for the 1-kWe flight system consists of a 4 kWt highly enriched uranium-molybdenum reactor operating at 800 degC coupled to sodium heat pipes. The heat pipes deliver heat to the hot ends of eight 125-W Stirling convertors producing a net electrical output of 1 kW. Waste heat is rejected using titanium-water heat pipes coupled to carbon composite radiator panels. The KRUSTY test, based on this design, uses a prototypic highly enriched uranium-molybdenum core coupled to prototypic sodium heat pipes. The heat pipes transfer heat to two Advanced Stirling Convertors (ASC−E2s) and six thermal simulators, which simulate the thermal draw of full-scale power conversion units. Thermal simulators and Stirling engines are gas cooled. The most recent project milestone was the completion of nonnuclear system-level testing using an electrically heated depleted uranium (DU) (nonfissioning) reactor core simulator at the NASA Glenn Research Center. System-level testing has validated performance predictions and has demonstrated system-level operation and control in a test configuration that replicates the one to be used at the Device Assembly Facility (DAF) at the NNSS. Fabrication, assembly, and testing of the DU core has allowed for higher fidelity system-level testing at Glenn, and has validated the fabrication methods to be used on the highly enriched uranium core that will supply heat for the DAF KRUSTY demonstration.

Briggs, Maxwell H.↗

Trade-offs between Biofuels Energy Production, Land Use and Water Use in Florida

Objective of the presentation is to document land use and water use implications of biomass production to demonstrate the overall resources implications associated with bioethanol production for Florida’s transportation sector needs. Rationale for using biofuels (BF) is explained, so are advantages & challenges of BF production and use. Land use changes (LUC) in Florida are presented and consequences outlined. It is documented that Florida’s agricultural land is a very limited resource, with only 0.43 ac/person comparing to the global average of 1.71 ac/person. The direct relation of increased biofuels production causing increased water use is explained. Favorable climate, water resources, advanced research, traditional leading agricultural role, minor oil reserves, no refineries and increasing energy demands are the main reasons why Florida considers pursuing BF production in large scale. Eight various bioethanol crops produced in Florida were considered in this study (Miscanthus, Switchgrass, Sweet Sorghum, Corn, Elephantgrass, Sugarcane, Energycane, Eucalyptus). Biomass yield and bioethanol yield of these crops are documented. Bioethanol needs of Florida are estimated and related land requirements for the needed bioethanol production calculated. Projections for various bioethanol blends (E15 to E85) are then presented. Finally, water demand for biofuels production is quantified. It is concluded that land use requirement for production of all ethanol in E85 fuel blend in Florida is roughly the same as the total available ag land in Florida for the best yielding biofuels crops (energycane, eucalyptus). Water demand for production of all ethanol needed for E100 would increase current overall water consumption in Florida between 65% and 100% for the most common biofuels crops. Vehicular energy is only 33% of Floridians energy consumption, so even all Florida’s agricultural land was given up for biofuels, it would still produce only 33% of Florida’s total energy needs. Still, bioethanol (primarily cellulosic) produced in Florida has a potential to meet a significant portion of the State’s transportation needs. Assuming no change in food production and consumption habits in Florida, the likely result of biofuels sector expansion would be the conversion of natural lands or low-intensity agricultural lands into high-intensity biomass production and the associated increased water consumption and water quality implications.

09 BIOMASS FUELS↗

Long-term nitrogen dioxide exposure assessment using back-extrapolation of satellite-based land-use regression models for Australia

Highlights: • We assessed how well a year-2006 satellite-based LUR model captures historical NO{sub 2}. • We used three methods to estimate annual mean NO{sub 2} during 1990–2005. • We measured their performance using standard LUR validation techniques. • Back-extrapolated 2006 levels captured up to 76% of spatial variability (90–05). Assessing historical exposure to air pollution in epidemiological studies is often problematic because of limited spatial and temporal measurement coverage. Several methods for modelling historical exposures have been described, including land-use regression (LUR). Satellite-based LUR is a recent technique that seeks to improve predictive ability and spatial coverage of traditional LUR models by using satellite observations of pollutants as inputs to LUR. Few studies have explored its validity for assessing historical exposures, reflecting the absence of historical observations from popular satellite platforms like Aura (launched mid-2004). We investigated whether contemporary satellite-based LUR models for Australia, developed longitudinally for 2006–2011, could capture nitrogen dioxide (NO{sub 2}) concentrations during 1990–2005 at 89 sites around the country. We assessed three methods to back-extrapolate year-2006 NO{sub 2} predictions: (1) ‘do nothing’ (i.e., use the year-2006 estimates directly, for prior years); (2) change the independent variable ‘year’ in our LUR models to match the years of interest (i.e., assume a linear trend prior to year-2006, following national average patterns in 2006–2011), and; (3) adjust year-2006 predictions using selected historical measurements. We evaluated prediction error and bias, and the correlation and absolute agreement of measurements and predictions using R{sup 2} and mean-square error R{sup 2} (MSE-R{sup 2}), respectively. We found that changing the year variable led to best performance; predictions captured between 41% (1991; MSE-R{sup 2} = 31%) and 80% (2003; MSE-R{sup 2} = 78%) of spatial variability in NO{sub 2} in a given year, and 76% (MSE-R{sup 2} = 72%) averaged over 1990–2005. We conclude that simple methods for back-extrapolating prior to year-2006 yield valid historical NO{sub 2} estimates for Australia during 1990–2005. These results suggest that for the time scales considered here, satellite-based LUR has a potential role to play in long-term exposure assessment, even in the absence of historical predictor data.

54 ENVIRONMENTAL SCIENCES↗

Characterization of zirconium carbides using electron microscopy, optical anisotropy, Auger depth profiles, X-ray diffraction, and electron density calculated by charge flipping method

Samples with five different zirconium carbide compositions (C/Zr molar ratio=0.84, 0.89, 0.95, 1.05, and 1.17) have been fabricated and studied using a variety of experimental techniques. Each sample was zone refined to ensure that the end product was polycrystalline with a grain size of 10-100 {mu}m. It was found that the lattice parameter was largest for the x=0.89 composition and smallest for the x=1.17 total C/Zr composition, but was not linear; this nonlinearity is possibly explained using electron densities calculated using charge flipping technique. Among the five samples, the unit cell of the ZrC{sub 0.89} sample showed the highest electron density, corresponding to the highest carbon incorporation and the largest lattice parameter. The ZrC{sub 0.84} sample showed the lowest carbon incorporation, resulting in a larger number of carbon vacancies and resultant strain. Samples with larger carbon ratios (x=0.95, 1.05, and 1.17) showed a slight decrease in lattice parameter, due to a decrease in electron density. Optical anisotropy measurements suggest that these three samples contained significant amounts of a graphitic carbon phase, not bonded to the Zr atoms. - Graphical abstract: Characterization of zirconium carbides using electron microscopy, optical anisotropy, Auger depth profiles, X-ray diffraction, and electron density calculated by the charge flipping method. Highlights: Black-Right-Pointing-Pointer The lattice parameter variation: ZrC{sub 0.89}>ZrC{sub 0.84}>ZrC{sub 0.95}>ZrC{sub 1.05}>ZrC{sub 1.17}. Black-Right-Pointing-Pointer Surface oxygen with no correlation to the lattice parameter variation. Black-Right-Pointing-Pointer ZrC{sub 0.89} had highest electron densities correspond to highest carbon incorporation. Black-Right-Pointing-Pointer Second highest lattice parameter in ZrC{sub 0.84} due to strain. Black-Right-Pointing-Pointer Unit cell electron density order: ZrC{sub 0.95}>ZrC{sub 1.05}>ZrC{sub 1.17}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automated correlative segmentation of large Transmission X-ray Microscopy (TXM) tomograms using deep learning

Highlights: • A unique automated segmentation approach for large 3D nanotomography datasets obtained by Transmission X-ray Microscopy (TXM) in an Al-Cu alloy. • Automated segmentation using a Convolutional Neural Network (CNN) architecture based on a deep learning approach was employed. • This extremely versatile technique is capable of emulating the manual segmentation process effectively. • Quantitative comparison between manual segmentation and CNN architecture established the accuracy of this automated technique. • Its ability to robustly process ultra-large volumes of data in relatively small time frames can exponentially accelerate tomographic data analysis. - Abstract: A unique correlative approach for automated segmentation of large 3D nanotomography datasets obtained using Transmission X-ray Microscopy (TXM) in an Al-Cu alloy has been introduced. Automated segmentation using a Convolutional Neural Network (CNN) architecture based on a deep learning approach was employed. This extremely versatile technique is capable of emulating the manual segmentation process effectively. Coupling this technique with post-scanning SEM imaging ensured precise estimation of 3D morphological parameters from nanotomography. The segmentation process as well as subsequent analysis was expedited by several orders of magnitude. Quantitative comparison between segmentation performed manually and using the CNN architecture established the accuracy of this automated technique. Its ability to robustly process ultra-large volumes of data in relatively small time frames can exponentially accelerate tomographic data analysis, possibly opening up novel avenues for performing 4D characterization experiments with finer time steps.

36 MATERIALS SCIENCE↗

Automated flaw detection scheme for cast austenitic stainless steel weld specimens using Hilbert-Huang transform of ultrasonic phased array data

The objective of this work is to develop processing algorithms to detect and localize flaws using ultrasonic phased-array data. Data was collected on cast austenitic stainless stell (CASS) weld specimens onloan from the U.S. nuclear power industry' Pressurized Walter Reactor Owners Group (PWROG) traveling specimen set. Each specimen consists of a centrifugally cast stainless stell (CCSS) pipe section welded to a statically cst(SCSS) or wrought (WRSS) section. The paper presents a novel automated flaw detection and localization scheme using low frequency ultrasonic phased array inspection singals from the weld and heat affected zone of the based materials. The major steps of the overall scheme are preprocessing and region of interest (ROI) detection followed by the Hilbert-Huang transform (HHT) of A-scans in the detected ROIs. HHT offers time-frequency-energy distribution for each ROI. The Accumulation of energy in a particular frequency band is used as a classification feature for the particular ROI.

36 MATERIALS SCIENCE↗

Nitrogen use efficiency evaluation of aerobic rice under field capacity water potential using {sup 15}N isotopic tracer technique

This study was carried out to evaluate the efficiency use of the nitrogen fertilizer on aerobic rice varieties MR219-4 and MR219-9 which were grown aerobically under field capacity water potential at the controlled environment area or shield house. Direct {sup 15}N isotope tracer method was used in this study, whereby the {sup 15}N isotope was utilized as a tracer for nitrogen nutrient uptake. {sup 15}N isotope presence in the samples is determined by using emission spectrometer analysis and percentage of total nitrogen is determined by using Kjeldahl method. {sup 15}N atom access value contained in the sample will be used in determining the effectiveness of the use of nitrogen in fertilizers through the specific calculation formulas. In this work, the data several data of nitrogen derived from fertilizer (Ndff), total nitrogen, nitrogen uptake and nitrogen use efficiency was obtained.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Using a conformation-dependent stereochemical library improves crystallographic refinement of proteins

The major macromolecular crystallographic refinement packages restrain models to ideal geometry targets defined as single values that are independent of molecular conformation. However, ultrahigh-resolution X-ray models of proteins are not consistent with this concept of ideality and have been used to develop a library of ideal main-chain bond lengths and angles that are parameterized by the {phi}/{psi} angle of the residue [Berkholz et al. (2009), Structure, 17, 1316-1325]. Here, it is first shown that the new conformation-dependent library does not suffer from poor agreement with ultrahigh-resolution structures, whereas current libraries have this problem. Using the TNT refinement package, it is then shown that protein structure refinement using this conformation-dependent library results in models that have much better agreement with library values of bond angles with little change in the R values. These tests support the value of revising refinement software to account for this new paradigm.

59 BASIC BIOLOGICAL SCIENCES↗

Top Quark Produced Through the Electroweak Force: Discovery Using the Matrix Element Analysis and Search for Heavy Gauge Bosons Using Boosted Decision Trees

The top quark produced through the electroweak channel provides a direct measurement of the V tb element in the CKM matrix which can be viewed as a transition rate of a top quark to a bottom quark. This production channel of top quark is also sensitive to different theories beyond the Standard Model such as heavy charged gauged bosons termed W'. This thesis measures the cross section of the electroweak produced top quark using a technique based on using the matrix elements of the processes under consideration. The technique is applied to 2.3 fb -1 of data from the D0 detector. From a comparison of the matrix element discriminants between data and the signal and background model using Bayesian statistics, we measure the cross section of the top quark produced through the electroweak mechanism σ(p$\bar{p}$ → tb + X, tqb + X) = 4.30 -1.20 +0.98 pb. The measured result corresponds to a 4.9σ Gaussian-equivalent significance. By combining this analysis with other analyses based on the Bayesian Neural Network (BNN) and Boosted Decision Tree (BDT) method, the measured cross section is 3.94 ± 0.88 pb with a significance of 5.0σ, resulting in the discovery of electroweak produced top quarks. Using this measured cross section and constraining |V tb | < 1, the 95% confidence level (C.L.) lower limit is |V tb | > 0.78. Additionally, a search is made for the production of W' using the same samples from the electroweak produced top quark. An analysis based on the BDT method is used to separate the signal from expected backgrounds. No significant excess is found and 95% C.L. upper limits on the production cross section are set for W' with masses within 600-950 GeV. For four general models of W{prime} boson production using decay channel W' → t$\bar{p}$, the lower mass limits are the following: M(W' L with SM couplings) > 840 GeV; M(W' R ) > 880 GeV or 890 GeV if the right-handed neutrino is lighter or heavier than W{prime}{sub R}; and M(W' L+R ) > 915 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Teaching Freight Mode Choice Models New Tricks Using Interpretable Machine Learning Methods

Understanding and forecasting the intricate freight mode choice behavior under various industry, policy, and technology contexts is essential in freight planning and policymaking. Numerous models have been developed in prior studies to provide insights into freight mode selection, the majority of which use discrete choice models such as multinomial logit (MNL) models. However, logit models often rely on linear specifications of independent variables, despite potential nonlinear relationships in the data. Moreover, there often lacks a heuristic and efficient approach to identify such complex relationships to define the logit model specifications. To fill this gap, we developed an MNL model for freight mode choice using the insights from state-of-the- art machine learning (ML) models. ML models can capture the nonlinear nature of the complex decision-making process, and recent advances in 'explainable AI' have greatly improved their interpretability. The interpretable ML methods help enhance the performance of MNL models and advance knowledge of freight mode choice. Specifically, the influential factors and their relationship with individual modes are identified using SHapley Additive exPlanations (SHAP) to improve the MNL's performance. The workflow is demonstrated in a case study of Austin, Texas, and the SHAP results reveal multiple nonlinear relationships predicted by ML models. Incorporating those relationships into MNL model specifications improves the interpretability and accuracy of the MNL model compared to a conventional MNL model. Findings from this study can be used to guide freight planning and inform policymakers and practitioners on how key factors affect freight decision-making.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗