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At least 469 records · Page 26

Review of the Aerodynamic Acceptance Test and Application to Anti-Icing Fluids Testing in the NRC Propulsion and Icing Wind Tunnel

In recent years, the FAA has worked with Transport Canada, National Research Council of Canada (NRC) and APS Aviation, Inc. to develop allowance times for aircraft operations in ice-pellet precipitation. These allowance times are critical to ensure safety and efficient operation of commercial and cargo flights. Wind-tunnel testing with uncontaminated anti-icing fluids and fluids contaminated with simulated ice-pellets had been carried out at the NRC Propulsion and Icing Wind Tunnel (PIWT) to better understand the flowoff characteristics and resulting aerodynamic effects. The percent lift loss on the thin, high-performance wing model tested in the PIWT was determined at 8 angle of attack and used as one of the evaluation criteria in determining the allowance times. Because it was unclear as to how performance degradations measured on this model were relevant to an actual airplane configuration, some means of interpreting the wing model lift loss was deemed necessary. In this report, the lift loss was related to the loss in maximum lift of a Boeing 737-200ADV airplane through the Aerodynamic Acceptance Test (AAT) performed for fluids qualification. This report provides a review of the research basis of the AAT in order to understand how this correlation was applied. A loss in maximum lift coefficient of 5.24 percent on the B737-200ADV airplane (which was adopted as the threshold in the AAT) corresponds to a lift loss of 7.3 percent on the PIWT model at 8 degrees angle of attack. There is significant scatter in the data used to develop the correlation related to varying effects of the various antiicing fluids that were tested and other factors. A statistical analysis indicated the upper limit of lift loss on the PIWT model was 9.2 percent. Therefore, for cases resulting in PIWT model lift loss from 7.3 to 9.2 percent, extra scrutiny of the visual observations is required in evaluating fluid performance with contamination. Additional research may result in future changes to this correlation.

Broeren, Andy P.↗

Consistency Between NASS Surveyed Soil Moisture Conditions and SMAP Soil Moisture Observations

The USDA National Agricultural Statistics Survey (NASS) collects and publishes crop growth status and soil moisture conditions in major US agricultural regions. The operationally-produced weekly reports are based on survey information. The surveys are based on visual assessments and ? in the case of soil moisture ? report soil moisture levels in one of four categories (Very Short, Short, Adequate and Surplus). In this study, we show that these reports have remarkable correspondence with the NASA Soil Moisture Active Passive (SMAP) Level-4 Soil Moisture (L4SM) product. This consistency allows the combining the two distinct types of data to produce a value-added combination, which is mapped fields rather than State-by-State tables and it is refreshed daily rather than weekly. In this study classification thresholds are derived for L4SM by mapping cumulative distribution functions of L4SM surface and root-zone SM to the categorical NASS SM conditions. The results show that, year-over-year, the SMAP cumulative SM distributions are consistent with the NASS SM conditions and, furthermore, that the temporal evolution of the SMAP-derived thresholds is consistent with the seasonal crop growth cycles from year to year. The results signify that the SMAP SM retrievals are relatable to SM estimation conducted in agriculture by land managers and farmers, which underlines the general applicability of the SMAP data.

Andreas Colliander↗

Asymmetric Flow State Switching in the Space Launch System Block 2 Liftoff Environment

An in-depth investigation was conducted at the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel to evaluate flow state switching in the liftoff flow environment of the Space Launch System Block 2 Crew launch vehicle using force measurements, two-component particle image velocimetry, and tuft flow visualization. Multimodal flow states were observed in the gap flow between the centerbody and solid rocket boosters at a range of incoming flow angles and were characterized for the relative strength of state switches. When flow switches occur, the flow is predominantly bimodal, but trimodal flow states are observed with the launch tower downstream of the vehicle. Tuft visualization indicates three-dimensionality during flow state switching, which initiates at one part of the gap and quickly transitions throughout the length of the booster. Due to the long time scales between switches, statistics such as frequency of flow state switches and converged state probabilities cannot be established without significantly increased acquisition times.

Lee J. Mears↗

Asymmetric Flow State Switching on the Space Launch System (SLS) Block 2 Crew Vehicle

An in-depth investigation was conducted at the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel to evaluate flow state switching in the liftoff flow environment of the Space Launch System Block 2 Crew launch vehicle using side force measurements, two-component particle image velocimetry, and tufts flow visualization. Multimodal flow states were observed in the gap flow between the centerbody and solid rocket boosters at a range of incoming flow angles and were characterized for the relative strength of state switches. When flow switches occur, the flow is predominantly bimodal, but trimodal flow states are observed with the launch tower downstream of the vehicle. Tufts visualization indicates three-dimensionality during flow state switching, which initiates at one part of the gap and quickly transitions throughout the length of the booster. Due to the long time scales between switches, statistics such as frequency of flow state switches and converged state probabilities cannot be established without significantly increased acquisition times.

Lee J. Mears↗

First Cloud-to-Ground Lightning Timing Study

NASA's LSP, GSDO and other programs use the probability of cloud-to-ground (CG) lightning occurrence issued by the 45th Weather Squadron (45 WS) in their daily and weekly lightning probability forecasts. These organizations use this information when planning potentially hazardous outdoor activities, such as working with fuels, or rolling a vehicle to a launch pad, or whenever personnel will work outside and would be at-risk from lightning. These organizations would benefit greatly if the 45 WS could provide more accurate timing of the first CG lightning strike of the day. The Applied Meteorology Unit (AMU) has made significant improvements in forecasting the probability of lightning for the day, but forecasting the time of the first CG lightning with confidence has remained a challenge. To address this issue, the 45 WS requested the AMU to determine if flow regimes, wind speed categories, or a combination of the two could be used to forecast the timing of the first strike of the day in the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) lightning warning circles. The data was stratified by various sea breeze flow regimes and speed categories in the surface to 5,000-ft layer. The surface to 5,000-ft layer was selected since that is the layer the 45 WS uses to predict the behavior of sea breeze fronts, which are the dominant influence on the occurrence of first lightning in Florida during the warm season. Due to small data sample sizes after stratification, the AMU could not determine a statistical relationship between flow regimes or speed categories and the time of the first CG strike.. As expected, although the amount and timing of lightning activity varies by time of day based on the flow regimes and speed categories, there are extended tails of low lightning activity making it difficult to specify times when the threat of the first lightning flash can be avoided. However, the AMU developed a graphical user interface with input from the 45 WS that allows forecasters to visualize the climatological frequencies of the timing of the first lightning strike. This tool should contribute directly to the 45 WS goal of improving lightning timing capability for its NASA, US Air Force and commercial customers.

statistical analysis↗

Explicit simulation of the Brownian rotation of arbitrary shaped aerosol particles using quaternions

The shape of an aerosol particle strongly influences its mass and momentum transfer cross-sections, charging properties, and other physical properties. Here, we present an explicit time-stepping procedure to simulate the rotational Brownian motion of arbitrary shaped aerosol particles by solving Euler’s equation of rotation. A Langevin formulation of the rotation equations is used, wherein Brownian motion due to thermal collisions between a particle and background gas molecules is represented using a stochastic fluctuating torque and fluid resistance is included as a drag torque. To avoid singularities associated with describing the orientation of a shape with Euler angles, we employ a quaternion formulation that leads to first-order stochastic differential equations to describe the evolution of the angular position and angular velocity of a rigid body. We perform all the rotational dynamics calculations in the body-fixed frame of reference attached to the rotating shape whose basis vectors are the normalized eigenvectors of the inertia tensor of the particle. Numerical solutions to rotation under torque-free conditions, damped rotation without Brownian motion, and stochastic rotation for arbitrary shapes are presented and discussed. The presented method enables time-resolved simulation of Brownian rotation for direct comparison with experimentally measured trajectories or statistical measures. The second order accuracy of the used time-stepping procedure places a severe restriction on the timestep that can be used for obtaining accurate results. Animations of presented simulations are included for visualizing rotational motion at various gas pressures. To aid implementation, MATLAB ® codes are also provided. Extension to include translation Brownian motion is straightforward.

Roy, Mrittika↗

SpotSDC: Revealing the Silent Data Corruption Propagation in High-Performance Computing Systems

We report the trend of rapid technology scaling is expected to make the hardware of high-performance computing (HPC) systems more susceptible to computational errors due to random bit flips. Some bit flips may cause a program to crash or have a minimal effect on the output, but others may lead to silent data corruption (SDC), i.e., undetected yet significant output errors. Classical fault injection analysis methods employ uniform sampling of random bit flips during program execution to derive a statistical resiliency profile. However, summarizing such fault injection result with sufficient detail is difficult, and understanding the behavior of the fault-corrupted program is still a challenge. In this article, we introduce SpotSDC, a visualization system to facilitate the analysis of a program's resilience to SDC. SpotSDC provides multiple perspectives at various levels of detail of the impact on the output relative to where in the source code the flipped bit occurs, which bit is flipped, and when during the execution it happens. SpotSDC also enables users to study the code protection and provide new insights to understand the behavior of a fault-injected program. Based on lessons learned, we demonstrate how what we found can improve the fault injection campaign method.

97 MATHEMATICS AND COMPUTING↗

Thermal- and plasma-induced molecular redistribution on the icy satellites

The molecular transport of condensed gas species across the surfaces of the icy satellites of Jupiter and Saturn is examined with the view of describing, in part, certain gross visual features associated with these bodies. Molecular redistribution induced by thermal sublimation and magnetospheric plasma-ion impact on satellites with negligible atmospheres is calculated by assuming that the molecules follow ballistic trajectories and by statistically selecting initial molecular velocities and points of origin. Erosion/deposition profiles so calculated are compared for a variety of satellite sizes and environments in order to understand the relative importance of sublimation and cold corotating plasma-ion- and fast plasma-ion-induced transport. The erosion/deposition profiles are used to discuss the appearance of a polar frost on Ganymede. A balance of magnetospheric-ion implantation and ion-induced molecular redistribution is used to discuss the observation of embedded SO2 and the darkening of the trailing side on Europa. Ion-induced molecular transport may also limit the deposition of SO2 frost in the polar regions of Io and may be a source of heavy particles in the Jovian and Saturnian magnetospheres.

Sieveka, E. M.↗

Report on the Global Data Assembly Center (GDAC) to the 12th GHRSST Science Team Meeting

In 2010/2011 the Global Data Assembly Center (GDAC) at NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) continued its role as the primary clearinghouse and access node for operational Group for High Resolution Sea Surface Temperature (GHRSST) datastreams, as well as its collaborative role with the NOAA Long Term Stewardship and Reanalysis Facility (LTSRF) for archiving. Here we report on our data management activities and infrastructure improvements since the last science team meeting in June 2010.These include the implementation of all GHRSST datastreams in the new PO.DAAC Data Management and Archive System (DMAS) for more reliable and timely data access. GHRSST dataset metadata are now stored in a new database that has made the maintenance and quality improvement of metadata fields more straightforward. A content management system for a revised suite of PO.DAAC web pages allows dynamic access to a subset of these metadata fields for enhanced dataset description as well as discovery through a faceted search mechanism from the perspective of the user. From the discovery and metadata standpoint the GDAC has also implemented the NASA version of the OpenSearch protocol for searching for GHRSST granules and developed a web service to generate ISO 19115-2 compliant metadata records. Furthermore, the GDAC has continued to implement a new suite of tools and services for GHRSST datastreams including a Level 2 subsetter known as Dataminer, a revised POET Level 3/4 subsetter and visualization tool, a Google Earth interface to selected daily global Level 2 and Level 4 data, and experimented with a THREDDS catalog of GHRSST data collections. Finally we will summarize the expanding user and data statistics, and other metrics that we have collected over the last year demonstrating the broad user community and applications that the GHRSST project continues to serve via the GDAC distribution mechanisms. This report also serves by extension to summarize the activities of the GHRSST Data Assembly and Systems Technical Advisory Group (DAS-TAG).

sea surface temperature (SST)↗

Deep Space Network-Wide Portal Development: Planning Service Pilot Project

The Deep Space Network (DSN) is an international network of antennas that supports interplanetary spacecraft missions and radio and radar astronomy observations for the exploration of the solar system and the universe. DSN provides the vital two-way communications link that guides and controls planetary explorers, and brings back the images and new scientific information they collect. In an attempt to streamline operations and improve overall services provided by the Deep Space Network a DSN-wide portal is under development. The project is one step in a larger effort to centralize the data collected from current missions including user input parameters for spacecraft to be tracked. This information will be placed into a principal repository where all operations related to the DSN are stored. Furthermore, providing statistical characterization of data volumes will help identify technically feasible tracking opportunities and more precise mission planning by providing upfront scheduling proposals. Business intelligence tools are to be incorporated in the output to deliver data visualization.

project development↗

The Transition from Thick to Thin Plate Wake Physics: Whither Vortex Shedding?

The near and very near wake of a flat plate with a circular trailing edge is investigated with data from direct numerical simulations. Computations were performed for six different combinations of the Reynolds numbers based on plate thickness (D) and boundary layer momentum thickness upstream of the trailing edge (theta). Unlike the case of the cylinder, these Reynolds numbers are independent parameters for the flat plate. The separating boundary layers are turbulent in all the cases investigated. One objective of the study is to understand the changes in the wake vortex shedding process as the plate thickness is reduced (increasing theta/D). The value of D varies by a factor of 16 and that of theta by approximately 5 in the computations. Vortex shedding is vigorous in the low theta/D cases with a substantial decrease in shedding intensity in the large theta/D cases. Other shedding characteristics are also significantly altered with increasing theta/D. A visualization of the shedding process in the different cases is provided and discussed. The basic shedding mechanism is explored in depth. The effect of changing theta/D on the time-averaged, near-wake velocity statistics is also discussed. A functional relationship between the shedding frequency and the Reynolds numbers mentioned above is obtained.

CFD↗

Supersonic Traveling Crossflow Wave Characteristics in Ground and Flight Tests

This paper continues analysis of data acquired in a series of supersonic crossflow transition experiments on a 65° swept- wing model tested in both wind tunnel and flight. Flow visualization data are summarized to provide context for the swept-wing instability mechanisms of interest. Unsteady pressure measurements obtained near the wing model leading edge (LE) are studied using 2nd- and 3rd-order statistical methods to extract traveling crossflow wave characteristics from these data. Comparisons between tunnel and flight data with boundary-layer (BL) Linear Stability Theory (LST) predictions provide insights into BL transition phenomena similarities and differences observed in tests using the same swept-wing model configurations. Comparisons of unsteady pressure data results for wing LE configurations with and without distributed-roughness-element (DRE) patterns installed, suggest traveling crossflow disturbance growth is reduced when this type of flow control is applied. A brief stud y of different background surface roughness levels on the wing LE suggests the potential for another flow control approach to promote laminar flow on swept wings using streamwise-biased surface finishes.

Lewis R Owens↗

On the Nature of AGN and Star Formation Enhancement in thez=3.1 SSA22Protocluster: The HST WFC3 IR View

We examine possible environmental sources of the enhanced star formation and active galactic nucleus (AGN) activity in the z=3.09 SSA22 protocluster using Hubble WFC3 F160W (∼1.6μm) observations of the SSA22 field, including new observations centered on eight X-ray selected protocluster AGN. To investigate the role of mergers in the observed AGN and star formation enhancement, we apply both quantitative (Sérsic-fit and Gini–M20)and visual morphological classifications to F160W images of protocluster Lyman-break galaxies (LBGs) in the fields of the X-ray AGN and z∼3field LBGs in SSA22 and GOODS-N. We find no statistically significant differences between the morphologies and merger fractions of protocluster and field LBGs, though we are limited by small number statistics in the protocluster. We also fit the UV-to-near-IR spectral energy distributions of F160W-detected protocluster and field LBGs to characterize their stellar masses and star formation histories. We find that the mean protocluster LBG is a factor of∼2 times more massive and more attenuated than the mean z∼3field LBG. We take our results to suggest that ongoing mergers are not more common among protocluster LBGs than field LBGs, though protocluster LBGs appear to be more massive. We speculate that the larger mass of the protocluster LBGs contributes to the enhancement of SMBH mass and accretion rate in the protocluster, which in turn drives the observed protocluster AGN enhancement

Erik B. Monson↗

A Scheme for finding the Front Boundary of an Interplanetary Magnetic Cloud

We developed a scheme for finding the front boundary of an interplanetary magnetic cloud (MC) based on criteria that depend on the possible existence of any one or all of six specific solar wind features. The features that the program looks for, within +/- 2 hours of a preliminarily determined time for the front boundary, estimated either by visual inspection or by an automatic MC identification scheme, are: (1) a sufficiently large directional discontinuity in the interplanetary magnetic field (IMF), (2) existence of a magnetic hole, (3) a significant proton plasma beta drop, (4) a significant proton temperature drop, (5) a marked increase in the IMF's intensity, and (6) a significant decrease in a normalized root-mean-square deviation (RMS)of the magnetic field - where the scheme was tested using 5, 10, 15, and 20 minute averages of the relevant physical quantities, in order to find the optimum average (and RMS) to use. Other criteria, besides these six, were examined and dismissed as not reliable, e.g., plasma speed. The scheme was developed specifically for aiding in forecasting the strength and timing of a geomagnetic storm due to the passage of an interplanetary MC in real-time, but can be used in post ground-data collection for imposition of consistency in choosing a MC's front boundary. The scheme has been extensively tested, first using 80 bona fide MCs over about 9 years of WIND data, and also for 121 MC-like structures as defined by a program that automatically identifies such structures over the same period. Optimum limits for various parameters in the scheme were found by statistical studies of the WIND MCs. The resulting limits can be user-adjusted for other data sets, if desired. Final testing of the 80 MCs showed that for 50 percent of the events the boundary estimates occurred within +/-10 minutes of visually determined times, 80 percent occurred within +/-30 minutes, and 91 percent occur within +/-60 minutes, and three or more individual boundary tests were passed for 88 percent of the total MCs. The scheme and its testing will be described.

Lepping, Ronald P.↗

Application of the Combined Judgmental and Randomly Placed Sampling Method

In the wake of the 2001 anthrax incidents in the United States, there has been considerable discussion about the role of judgmental and probabilistic sampling strategies, particularly in the context of clearance sampling. The Combined Judgmental and Random (CJR) methodology provides a statistical methodology that allows practitioners to leverage information from both judgmental and randomly selected sample locations and then quantify the confidence in negative results. The objective of the CJR sampling design is to demonstrate, with high probability, that a high percentage of the decision area (or population) is acceptable, given that none of the samples are unacceptable. The purpose of this document is to assist practitioners to appropriately use the CJR methodology and to implement this sampling design in Visual Sample Plan (VSP). We begin by defining some fundamental terms. A decision area is the geographical or spatial area (indoor or outdoor) about which practitioners wish to draw a conclusion on the basis of sampling and other relevant information. Decision areas typically include all or part of a building, but they may be any contaminated (or potentially contaminated) area for which characterization or clearance is required. In this report, a statistical sampling approach refers to any sampling approach based on a mathematical or statistical model that provides confidence or probability statements about the decision area. Statistical sampling approaches typically involve taking samples at random locations, or at the nodes of a randomly located grid or lattice that is superimposed on the decision area. The term probabilistic sampling is often used to describe statistical sampling designs that exclusively use randomly located samples. This terminology implies that probabilistic statements can only be made based upon the results of randomly placed samples. However, the CJR method utilizes a Bayesian model that gives rise to a formal probabilistic statement regarding the acceptability of the decision area based upon the information obtained from both judgmental and random samples. Judgmental samples play a vital role in the characterization and clearance process because they include the informed prior belief and expert knowledge of personnel involved in the sampling process.

97 MATHEMATICS AND COMPUTING↗

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Infectious diseases (IDs) have a significant detrimental impact on global health. Timely and accurate ID forecasting can result in more informed implementation of control measures and prevention policies. To meet the operational decision-making needs of real-world circumstances, we aimed to build a standardized, reliable, and trustworthy ID forecasting pipeline and visualization dashboard that is generalizable across a wide range of modeling techniques, IDs, and global locations. We forecasted 6 diverse, zoonotic diseases (brucellosis, campylobacteriosis, Middle East respiratory syndrome, Q fever, tick-borne encephalitis, and tularemia) across 4 continents and 8 countries. We included a wide range of statistical, machine learning, and deep learning models (n=9) and trained them on a multitude of features (average n=2326) within the One Health landscape, including demography, landscape, climate, and socioeconomic factors. The pipeline and dashboard were created in consideration of crucial operational metrics—prediction accuracy, computational efficiency, spatiotemporal generalizability, uncertainty quantification, and interpretability—which are essential to strategic data-driven decisions. While no single best model was suitable for all disease, region, and country combinations, our ensemble technique selects the best-performing model for each given scenario to achieve the closest prediction. For new or emerging diseases in a region, the ensemble model can predict how the disease may behave in the new region using a pretrained model from a similar region with a history of that disease. The data visualization dashboard provides a clean interface of important analytical metrics, such as ID temporal patterns, forecasts, prediction uncertainties, and model feature importance across all geographic locations and disease combinations. As the need for real-time, operational ID forecasting capabilities increases, this standardized and automated platform for data collection, analysis, and reporting is a major step forward in enabling evidence-based public health decisions and policies for the prevention and mitigation of future ID outbreaks.

60 APPLIED LIFE SCIENCES↗

Data Summarization and Inference at Scale

This is the final report for the DOE ASCR grant SC-0022260, Data Summarization and Inference at Scale, PI: Alex Pothen, Purdue University. The goal of the project was to solve data-intensive and compute-intensive problems in the physical sciences, engineering, information science, data science, etc. by designing and implementing new algorithms that could work with a subset of the data. The four subgoals were: (a) The solution of problems where the data is too large to be stored in the memory of a computer. In this streaming model of computation, the data arrives as a stream of elements to the computer, each element is processed as it arrives, and a decision is made to discard the data or to store it; only a small subset of the data proportional to the size of the output solution is stored, and when all the data has been streamed, a solution to the problem is computed from the stored subset. (b) The use of machine learning methods to compute solutions to data-intensive problems. The use of GPUs is critical to obtain high performance on machine learning tasks, but their memory sizes are smaller relative to that of CPUs. For large-scale problems, the data is sampled many times, and small samples are used with repetition, for robustness, to compute solutions to inference tasks. This sampling reduces the memory required to solve the problem, but attention is needed to avoid slow convergence to the solutions, and reduced accuracy of inference. We propose submodular optimization, Large Language Models, and physics-informed neural networks to enable GPU computations here. (c) Modeling and visualization of high-dimensional data using interpretable features. Clinical proteomic data sets from immunology for the detection of cancer and other diseases are temporal and high-dimensional, and algorithms for visualizing these data sets using clinically interpretable features are lacking. We propose methods that compute distances based on the optimal transportation problem and graph edit distances to address this problem. We also propose the use of optimal transport-based distances, spatial statistics, and network structure to classify image data sets, We apply these algorithms to electron micrographs of the peripheral nervous system in the digestive tract. (d) The design of data-intensive algorithms on emerging architectures, specifically, noisy, intermediate-scale quantum (NISQ) devices. Quantum computers offer the possibility of exploring large solution spaces due to the principle of superposition, but current quantum computers are limited by few qubits, short coherence times due to noise, poor interconections among the qubits, etc. We propose the use of the divide and conquer paradigm to solve large-scale problems, wherein collections of small subproblems are solved on the quantum devices, and the solutions to the subproblems are integrated into a solution for the original problem on a classical computer.

97 MATHEMATICS AND COMPUTING↗

Heavy-Duty Vehicle Port Drayage Drive Cycle Characterization and Development

In an effort to better understand the operational requirements of port drayage vehicles and their potential for adoption of advanced technologies, National Renewable Energy Laboratory (NREL) researchers collected over 36,000 miles of in-use duty cycle data from 30 Class 8 drayage trucks operating at the Port of Long Beach and Port of Los Angeles in Southern California. These data include 1-Hz global positioning system location and SAE J1939 high-speed controller area network information. Researchers processed the data through NREL's Drive-Cycle Rapid Investigation, Visualization, and Evaluation tool to examine vehicle kinematic and dynamic patterns across the spectrum of operations. Using the k-medoids clustering method, a repeatable and quantitative process for multi-mode drive cycle segmentation, the analysis led to the creation of multiple drive cycles representing four distinct modes of operation that can be used independently or in combination. These drive cycles are statistically representative of real-world operation of port drayage vehicles. When combined with modeling and simulation tools, these representative test cycles allow advanced vehicle or systems developers to efficiently and accurately evaluate vehicle technology performance requirements to reduce cost and development time while ultimately leading to the commercialization of advanced technologies that meet the performance requirements of the port drayage vocation. The drive cycles, which are suitable for chassis dynamometer testing, were compared to several existing test cycles. This paper presents the clustering methodology, accompanying results of the port drayage duty cycle analysis and custom drive cycle creation.

33 ADVANCED PROPULSION SYSTEMS↗