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At least 289 records · Page 16

BOLT-2 Roughness Side Flight Data Results and Analysis

This report provides an in-depth review of the flight data obtained from Side B, also known as the roughness side, of BOLT-2, which was developed and designed to measure the effectiveness of boundary layer trips at hypersonic conditions. Three discrete-roughness trips were implemented on Side B at specific locations, with the necessary sensor layout, to investigate the flight conditions at which they no longer maintained turbulence behind them. All three trips were the same type that were scaled and sized based on predictions of local boundary layer thicknesses to provide the same level of effectiveness. One trip was on the vehicle centerline, where the boundary layer is relatively thick, while the other two were symmetrically located outboard where the boundary layer is much thinner. The relative difference in boundary layer thickness between these locations was roughly on the order of 3-to-1, thus the centerline trip was geometrically about three times larger than the outboard trips. A first order assessment of the Side B flight results is indicated by these three trips forcing transition onset at the same time during flight. The enclosed flight data shows that the performance of each individual trip was nearly identical, with allowances for minor variations attributed to measurement accuracy.

Flight Data↗

Implementation of a realistic artificial data generator for crash data generation

In this paper, a framework is outlined to generate realistic artificial data (RAD) as a tool for comparing different models developed for safety analysis. The primary focus of transportation safety analysis is on identifying and quantifying the influence of factors contributing to traffic crash occurrence and its consequences. The current framework of comparing model structures using only observed data has limitations. With observed data, it is not possible to know how well the models mimic the true relationship between the dependent and independent variables. Further, real datasets do not allow researchers to evaluate the model performance for different levels of complexity of the dataset. RAD offers an innovative framework to address these limitations. Hence, we propose a RAD generation framework embedded with heterogeneous causal structures that generates crash data by considering crash occurrence as a trip level event impacted by trip level factors, demographics, roadway and vehicle attributes. Within our RAD generator we employ three specific modules: (a) disaggregate trip information generation, (b) crash data generation and (c) crash data aggregation. For disaggregate trip information generation, we employ a daily activity-travel realization for an urban region generated from an established activity-based model for the Chicago region. We use this data of more than 2 million daily trips to generate a subset of trips with crash data. For trips with crashes crash location, crash type, driver/vehicle characteristics, and crash severity. The daily RAD generation process is repeated for generating crash records at yearly or multi-year resolution. In conclusion, the crash databases generated can be employed to compare frequency models, severity models, crash type and various other dimensions by facility type - possibly establishing a universal benchmarking system for alternative model frameworks in safety literature.

42 ENGINEERING↗

Mobility Gaps between Low-Income and Not Low-Income Households: A Case Study in New York State

Understanding the travel challenges faced by low-income residents has always been and continues to be one of the most important transportation equity topics. This study aims to explore the mobility gaps between low-income households (HHs) and not low-income HHs, and how the gaps vary within different socio-demographic population groups in New York State (NYS). The latest National Household Travel Survey data was used as the primary data source for the analysis. The study first employed the K-prototype clustering algorithm to categorize the HHs in NYS based on their socio-demographic attributes. Five population groups were identified based on nine different household (HH) features such as HH size, vehicle ownership, and elderly status of its members. Then, the mobility differences, measured by trip frequency, trip distance, travel time, and person miles traveled, were examined among the five population groups. Results suggest that the individuals in low-income HHs consistently took fewer trips and made shorter trips compared to their not low-income counterparts in NYS. The travel distance gaps were most obvious among white HHs with more vehicles than drivers. In addition, while the population from low-income HHs made shorter trips on average (2.7 mi shorter per trip), they experienced longer travel time than those from not low-income HHs (1.8 min longer per trip). These key findings provide a deeper understanding of the travel behavior disparities between low-income and not low-income households. The findings could also support policymakers and transportation planners in addressing the critical needs of residents in low-income households in NYS and provide inputs for designing a more equitable transportation system.

Liu, Yuandong↗

Transit Rider/Travel Behavior Inventory Survey - Minneapolis-St. Paul Metro - 1990

The 1990 transit on-board survey aimed to update the 1988 survey, which was conducted as part of the Preliminary Engineering Study for the Hennepin County Light Rail Transit System. The 1988 study received Regional Transit Board funding, and survey results could be applied to a mode split model for projecting ridership on the proposed Light Rail Transit System. However, this survey was designed with the 1990 Travel Behavior Inventory in mind. The intention had been to update the 1988 survey in 1990 to be compatible with the 1990 Travel Behavior Inventory data. The results of the 1990 survey were used primarily to create a table of observed transit trips between each of the 1,200 traffic analysis zones in the region. This trip table was used to calibrate a new mode split model, which estimated future year travel by mode. The 1990 update survey focused on new routes and routes that had changed significantly since 1988. To preserve compatibility with the 1988 survey, the same survey questionnaire card was used, together with the same survey procedures for data collection. The procedures randomly sampled bus patrons during the transit trip, asking key questions about the patron and the transit trip. The survey card was intended for patrons to fill out quickly so it could be completed during the transit trip. The questions focused on conditions that have proven over time to significantly influence ridership. In all, a total of 20,126 valid survey records were processed. Adding surrogate trips, the survey data file is composed of a total of 27,159 trip records . About 10% of the records were filled out by persons who had answered more than one questionnaire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The structure of separated flow regions occurring near the leading edge of airfoils, including transition

Data was obtained for the NACA 663-018 airfoil in order to assess the advantages of tripping the boundary layer very near the leading edge for chord Reynolds numbers between 40,000 and 200,000. Single element trips were made from tape 2.5 mm wide and 0.15 mm thick. The unmodified tape trip in five thicknesses was placed across the span at 1.1% chord and the results of lift and drag measurements compared with the smooth airfoil case. Saw tooth geometry trips were also cut from tape and studied using five thicknesses. The saw tooth trips were placed across the span with the sharp points facing upstream at 1.1% chord and with the valley of the teeth at the 2.5% chord position. A large number of bumps and wiggles were produced in the lift coefficient versus angle of attack curves with various combinations of Reynolds number, thickness, and type of trips. The main result in the drag coefficient was an increase in C sub d min with increase in trip thickness.

Mueller, T. J.↗

Preparing for Mars: the physiologic and medical challenges

As the twentieth century closes, retrospectives cite the Apollo moon missions as one of the important events of the past 100 years. A trip to Mars, however, would be even more challenging and significant. A round-trip Mars journey would require nearly three years away from Earth, a significant leap in complexity compared to the two week long Moon trips or the record-breaking fourteen-month flight on Mir. What would be the physiologic and medical challenges of a Mars flight? Two key areas of physiology present the greatest potential problems--calcium metabolism and radiation exposure. Data from Mir missions show that bone loss continues in space despite an aggressive countermeasure program. Average losses were 0.35% per month, but some load bearing areas lost >1% per month. A 1% loss rate, if it continued unabated for 30 months, could produce osteoporosis. Smaller losses could still increase fracture risk. Some bone loss can be well tolerated, particularly if the bone can be regained after the mission. But the effectiveness of post-flight rehabilitation to restore the density and quality of bone after spaceflight is not well known. Bone loss estimates are based on continuous weightlessness exposure, but this is not a requirement for a Mars trip. Most of the time on a Mars trip will be spent in the 1/3 Earth's gravity environment on Mars, and either intermittent or continuous artificial gravity can be provided for the transit between planets (although at an engineering cost). The dosing of the gravity exposure (e.g. the level and duration), however, has not been established. Radiation protection also requires a balance between engineering cost and human health. Excessive shielding could add billions of dollars to the cost of a mission. Trips in interplanetary space, however, expose the crew to heavy high-energy particles from cosmic rays (HZE particles), which have a high linear energy transfer. This high energy leads to significant biological damage (e.g. chromosomal aberrations, cancer induction). A recent report from the Committee on Space Biology and Medicine notes that only one systematic study of cancer induction from high-energy particles has been conducted (using the mouse Harderian gland). Predictions of cancer risk and acceptable radiation exposure in space are extrapolated from minimal data. Other areas of physiology also present problems, such as muscle loss, cardiovascular deconditioning, and vestibular adaptation. Despite all the issues, however, a focussed, aggressive research program that uses the resources of the International Space Station should pave the way for mankind's greatest adventure--a trip to Mars.

STS-90 Shuttle Project↗

Hypersonic Laminar Boundary Layer Velocimetry with Discrete Roughness on a Flat Plate

Laminar boundary layer velocity measurements are made on a 10-degree half-angle wedge in a Mach 10 flow. Two types of discrete boundary layer trips were used to perturb the boundary layer gas. The first was a 2-mm tall, 4-mm diameter cylindrical trip. The second was a scaled version of the Orbiter Boundary Layer Transition (BLT) Detailed Test Objective (DTO) trip. Both 1-mm and 2.5-mm tall BLT DTO trips were tested. Additionally, side-view and plan-view axial boundary layer velocity measurements were made in the absence of these tripping devices. The free-stream unit Reynolds numbers tested for the cylindrical trips were 1.7x10(exp 6)/m and 3.3x10(exp 6)/m. The free-stream unit Reynolds number tested for the BLT DTO trips was 1.7x10(exp 6)/m. The angle of attack was kept at approximately 5-degrees for most of the tests resulting in a Mach number of approximately 8.3. These combinations of unit Reynolds numbers and angle of attack resulted in laminar flowfields. To study the precision of the measurement technique, the angle of attack was varied during one run. Nitric-oxide (NO) molecular tagging velocimetry (MTV) was used to obtain averaged axial velocity values and associated uncertainties. These uncertainties are as low as 20 m/s. An interline, progressive scan CCD camera was used to obtain separate images of the initial reference and shifted NO molecules that had been tagged by the laser. The CCD configuration allowed for sub-microsecond sequential acquisition of both images. The maximum planar spatial resolution achieved for the side-view velocity measurements was 0.07-mm in the wall-normal direction by 1.45-mm in the streamwise direction with a spatial depth of 0.5-mm. For the plan-view measurements, the maximum planar spatial resolution in the spanwise and streamwise directions was 0.69-mm by 1.28-mm, respectively, with a spatial depth of 0.5-mm. Temperature sensitive paint (TSP) measurements are provided to compliment the velocity data and to provide further insight into the behavior of the boundary layers. The experiments were performed at the NASA Langley Research Center 31-Inch Mach 10 Air tunnel.

Bathel, Brett↗

Key Differences in Operating a Rover on the Moon vs. Mars

The command and control model for spacecraft operations, as well as the distribution of tasks between ground assets and in space assets, whether with a crew or solely robotic, is fundamentally constrained by the round trip light time between the space asset and the control facility (presumably on Earth, though not required). For an asset on Mars, the round trip light time varies, from roughly fourteen minutes to up to forty minutes. For a Lunar asset the round-trip light time is measured in only a few seconds, but current communications systems may more than double the latency with system overhead. For a Lunar Asset the total command latency may range from six seconds to more than forty, depending on communications overhead and data rates. Further, these variables are not always predictable, thus complicating operations. There are several differentiating factors for Lunar vs. Mars operations, Round trip light time/Atmosphere/Lighting and ShadowsTerrain type and knowledge/Round trip light time has implications for the distribution of tasks between ground and in space assets. Even at Lunar Distances, the combination of round trip light time plus communications systems overhead does not enable joy stick driving of a rover. The best that can be done, if driving from Earth, is near real time command and control. By 2030, driving from in space may be possible. Productivity on Mars requires either long operational sequences of commands, as is done for current rovers such as Curiosity, significant autonomous capability or, as may be possible by 2030, command and control support from space. Another implication of the long round trip light time from Earth to Mars, is that flight software functions must be resident on the in space asset. On the Moon, there is considerably more flexibility, enabling processing functions, to be resident on Earth or in space. This provides the opportunity to take advantage of the considerable processing power available on the ground, but may be constrained by data rates. On the Moon, for practical operational purposes, there is no atmosphere. Hence there is no scattering of light in the shadows. This has implications for image interpretation and driving near the poles. The Moon has permanently shadowed regions (PSR), unique terrain with unknown surface properties. With no scattering of light in shadows, driving on the Moon, particularly at the poles, where we have strong evidence of water, may prove to be hazardous and complex, requiring non-optical sensors, such as LIDAR.

Trimble, Jay↗

Shockwave/Boundary-Layer Interaction Studies Performed in the NASA Langley 20-Inch Mach 6 Air Tunnel

This paper highlights results from a collaborative study performed by The University of Tennessee Space Institute (UTSI) and NASA Langley Research Center on the Shockwave/Boundary-Layer Interaction (SWBLI) generated by a cylindrical protuberance on a flat plate in a Mach 6 flow. The study was performed in the 20-Inch Mach 6 Air Tunnel at NASA Langley Research Center and consisted of two separate entries. In the first entry, simultaneous high-speed schlieren and high-speed pressure-sensitive paint (PSP) imaging – which was performed for the first time in the 20-Inch Mach 6 facility at NASA Langley – were performed as well as simultaneous high-speed schlieren and oil-flow imaging. In the second entry, the model configuration was modified to increase the size of the interaction region. High-speed schlieren and infrared thermography (IR) surface imaging were performed in this second entry. The goal of these tests was to characterize the SBLI in the presence of a laminar, transitional, and turbulent boundary layer using high-speed optical imaging techniques. AoA = sting angle-of-attack (°) dcylinder = cylinder diameter (mm) dtrip = cylindrical tripping element diameter (mm) Δshock = shock stand-off distance (mm) hcylinder = cylinder height (mm) htrip = cylindrical tripping element height (mm) HSS = high-speed schlieren M∞ = freestream Mach number PSP = pressure-sensitive paint Re∞ = freestream unit Reynolds number (m-1) SWBLI = shockwave/boundary-layer interaction θplate = model plate angle (°) Introduction his paper highlights two experimental entries performed in the 20-Inch Mach 6 Air Blowdown Tunnel at NASA Langley Research Center in collaboration with The University of Tennessee Space Institute (UTSI). The purpose of these entries was to characterize the dynamic shockwave/boundary-layer interaction (SWBLI) between a vertical cylinder on a flat plate and laminar, transitional (XSWBLI), and turbulent (SWTBLI) boundary layers with a freestream Mach number of 6 using non-intrusive optical diagnostics. Experiments performed by Murphree et al.1,2 were among the first to specifically characterize XSWBLI induced by a vertical cylinder on a flat plate geometry using several optical measurement techniques. Recent optical studies of XSWBLI phenomenon have been performed by UTSI at Mach 2 in their low-enthalpy blow wind tunnel3-8 and by Texas A&M University and UTSI at Mach numbers of 6 and 7 in their Adjustable Contour Expansion wind tunnel.9 The experiments described in this paper were intended to complement previous studies by expanding the freestream unit Reynolds number range, Re∞, over which the XSWBLI phenomena has been observed. Additionally these experiments, made possible under NASA’s new facility funding model under the Aeronautics Evaluation and Test Capabilities (AETC) project, promoted collaboration between university and NASA researchers. The initial entry in the 20-Inch Mach 6 Air Tunnel at NASA Langley occurred in December of 2016. Originally, testing was to occur in November of 2016 in the 31-Inch Mach 10 Air Tunnel at NASA Langley. This facility was chosen so that the XSWBLI phenomenon could be observed at much higher Mach numbers than had previously been attempted in ground test experiments. The model selected for this experiment, a 10° half-angle wedge with a sharp leading edge (described in detail in section II.B), had previously been used by Danehy et al. [10] for boundary layer transition studies using the nitric oxide planar laser-induced fluorescence (NO PLIF) flow visualization technique. In that work, it was determined that transition could be induced downstream of a single htrip = 1-mm tall, dtrip = 4-mm diameter cylindrical tripping element and that the streamwise location of the transition could be changed for a single Re∞ by changing the model angle-of-attack (AoA) (see Fig. A3 in Ref. [10] for more details). Based on the findings of that work, a decision was made to use the wedge model with the cylindrical tripping element to trip the boundary layer flow ahead of a cylindrical protuberance in order to achieve a XSWBLI. Unfortunately, the 31-Inch Mach 10 facility had been taken offline for repairs in October of 2016 and a decision was made to move the test to the 20-Inch Mach 6 facility. Since the behavior of the boundary layer with the chosen model configuration had not been studied before in that facility and the available test time was limited, the entry was considered to be exploratory and was used to collect spatially-resolved and time-resolved flow and surface visualization data that would be used to inform a second entry. Test techniques included simultaneous high-speed schlieren (HSS) captured at 160 kHz and high-speed pressure sensitive paint captured at 10 kHz as well as oil flow visualization, captured at 750 Hz. The second entry in the 20-Inch Mach 6 facility occurred in June and July of 2017. In this follow-on test, modifications to the wind tunnel model were made based on observations made during the first entry and included removing the cylindrical tripping element, increasing the size of the cylinder used to induce the SWBLI to increase the size of the interaction while simultaneously improving spatial resolution, and using a swept ramp array, similar to that described in Ref. [11], to trip the flow to turbulence. Simultaneous HSS (captured at 140 kHz, 100 kHz, and 40 kHz) and conventional IR thermography (captured at 30 Hz) imaging were performed simultaneously in this follow-on entry. This paper is intended to serve as a summary of the work performed during these two entries, to detail lessons learned from each entry, and to highlight some of the datasets acquired. Details on the experimental setup, model configuration, and techniques used are provided. Papers providing a more rigorous analysis of data acquired during the second entry, including statistical, spectral, and modal decomposition methods, can be found in Refs. [12,13]. An entry examining XSWBLI in the 31-Inch Mach 10 Blowdown Wind Tunnel facility is currently planned for mid-to-late calendar year 2019, pending the success of facility repairs. The work performed and described in this paper and the upcoming entry in the 31-Inch Mach 10 facility at NASA Langley have been made possible by NASA’s new facility funding model under the Aeronautics Evaluation and Test Capabilities (AETC) project. Wind Tunnel Facility All experiments discussed in this paper were performed in the 20-Inch Mach 6 Air Tunnel at NASA Langley Research Center. Specific details pertaining to this facility can be found in Refs. [14,15], with only a brief description of the facility provided here. For both entries, the nominal freestream unit Reynolds number was varied between 1.8×106 m-1 (0.5×106 ft-1) and 26.3×106 m-1 (8×106 ft-1). The nominal stagnation pressure was varied between 0.21 MPa and 3.33 MPa and the nominal stagnation temperature was varied between 480 K and 520 K to achieve the desired Re∞ condition. For all runs, the nominal freestream Mach number was 6. The nearly square test section is 520.7-mm (20.5-inches) wide by 508-mm (20-inches) high. Two 431.8-mm (17-inch) diameter windows made of Corning 7940, Grade 5F schlieren-quality glass serve as the side walls of the tunnel and provide optical access for the high-speed schlieren measurements. A rectangular window made of the same material as the side windows served as the top wall of the test section and provided optical access for the high-speed PSP and oil flow measurements. For the second entry, this top window was replaced with a Zinc Selenide (ZnSe) window with an anti-reflection coating capable of passing IR wavelengths between 8μm and 12μm with greater than 98% transmittance. The model was sting supported by a strut attached to a hydraulic system that allows for the model pitch angle to be adjusted between -5° to +55°. For the first entry, an initial pitch/pause sweep of the model AoA was performed to observe the resulting SWBLI. Ultimately, however, the sting pitch angle for this entry was fixed at +10.0° so that the angle of the top surface of the wedge relative to the streamwise axis of the tunnel (referred to herein as the plate angle, θplate), was θplate = 0°. For the second entry, θplate = 0° and θplate = -13.25° were initially tested with the swept ramp array (discussed in the following section) to determine which orientation produced conditions most favorable for XSWBLI to occur based on the heating signatures observed over the top surface of the model in the IR thermography images. Based on these initial tests, θplate = -13.25° was set for the remainder of the runs in the second entry. For both entries, any model changes were performed in a housing located beneath the closed test section. Prior to performing a run of the tunnel, the housing was sealed and the tunnel started. Once the appropriate freestream conditions were achieved, the model was injected into the test section using a hydraulic injection system. B. Model Geometry For all runs, a 10° half-angle (20° full-angle) wedge model with a sharp leading edge was used. The model is described in detail in Refs. [10,16]. The top surface of the sharp leading edge of the model extended 47.8 mm from its upstream-most edge to a junction with the upstream edge of a stainless steel top plate that then extended an (a) (c) (b) Fig. 1 (a) Schematic of top surface of wedge model with gas seeding insert, (b) perspective view of the model in the 20-Inch Mach 6 tunnel with centerline pressure orifices on sharp leading edge, and (c) a perspective view of the model with stainless steel (top) and SLA middle insert (bottom) during the first entry. Flow occurs from left to right.

Bathel, Brett F.↗

BOLT II Roughness-Side Flight Results

An initial review of the roughness data from the BOLT II flight is provided. The BOLT II roughness experiment was designed to investigate discrete trips in flight based on the diamond configuration, which has been shown to be an efficient vortex generator and boundary layer trip from extensive ground-based testing. There were three trip locations chosen for the flight test and their size (height and width) were tailored to the local boundary layer thickness, but all three were expected to trip at the same time or flight condition. Details about the flight vehicle design, instrumentation, and best estimated trajectory are discussed. The present paper is limited to only a review and analysis of the thermocouple data. Boundary layer transition onset times are derived from the thermocouple analysis, thus allowing an initial assessment of the performance of these discrete trips. Since the three trips were sized to trip the boundary layer at the same time, based on a previous wind tunnel study, the present analysis indicates that they performed as expected.

Hypersonic↗

Learning From User Behavior: A Survey-Assist Algorithm for Longitudinal Mobility Data Collection

GPS-based travel surveys are widely used in mobility studies to gather crucial qualitative data, like purpose, transportation mode and replaced mode. However, survey response still poses a burden to users, especially in long-term mobility studies, leading to response fatigue. We explore a survey-assist strategy to ease this burden by a novel, user-level modeling approach that leverages past responses from each user to predict responses for new trips, without relying on external data sources like GIS data. We investigate three main algorithms for predicting responses: (i) clustering trips and extrapolating responses for similar trips, (ii) using random forest classification, and (iii) clustering that uses a hybrid algorithm to determine spatial structure, which is then fed as input to a classic random forest classifier. The clustering approach can flexibly predict responses for even complex qualitative survey questions; it achieved F-scores of 65%. The random forest pipeline uses architecture that restricts it to predicting three predetermined survey questions: trip purpose, mode, and replaced mode. However, it achieved F-scores of 78%. While the survey-assist approach has been implemented by several proprietary systems, to our knowledge, this is the first exploration in the academic literature. It follows that this is also the first rigorous evaluation of multiple algorithms that can implement the approach. The evaluation uses a large scale, publicly available, longitudinal dataset consisting of ~ 92k trips from 235 users over a period of roughly one and a half years. With this approach, travel surveys can be pre-filled with the predicted responses for each trip, thus streamlining the survey process for users. Combined with an active learning system that requests user input on low-confidence predictions, models can be updated and improved over time to better support the long-term collection of longitudinal qualitative data.

clustering↗

In-Situ Observation of FCC→HCP Transformation-Induced Plasticity Behavior During Dynamic Deformation of CoCrNi Multi-principal Element Alloys

CoCrNi multi-principal element alloys (MPEAs) have potential as high toughness, blast resistant materials, but limited studies of their high strain rate behavior have been performed. Their high toughness has been attributed to low stacking fault energies and the activation of toughness enhancing deformation mechanisms, such as twinning- and transformation-induced plasticity (TWIP and TRIP, respectively), that may be affected by increased strain rate. This work examines a series of CoCrNi MPEAs tested with a miniaturized pressure bar, while simultaneous synchrotron x-ray diffraction and imaging are performed, and compares these results to those collected during quasi-static deformation at elevated temperatures. Here, the collected diffraction indicates that TRIP was active at elevated strain rates for the most Co-rich alloys containing 50 or 55 at. pct. Co, while TRIP behavior was suppressed at elevated strain rates in a 40 at. pct. Co alloy anticipated to experience TRIP. The suppression of TRIP in the lower Co alloy at high strain rates is attributed to adiabatic heating, consistent with suppression of TRIP as a result of elevated temperatures.

36 MATERIALS SCIENCE↗

Use of Shared Automated Vehicles for First-Mile Last-Mile Service: Micro-Simulation of Rail-Transit Connections in Austin, Texas

Shared fleets of fully automated vehicles (SAVs) coupled with real-time ride-sharing to and from transit stations are of interest to cities and nations in delivering more sustainable transportation systems. By providing first-mile last-mile (FMLM) connections to key transit stations, SAVs can replace walk-to-transit, drive-to-transit, and drive-only trips. Using the SUMO (Simulation of Urban MObility) toolkit, this paper examines mode splits, wait times, and other system features by micro-simulating two fleets of SAVs providing an FMLM ride-sharing service to 10% of central Austin’s trip-makers near five light-rail transit stations. These trips either start or end within two geofenced areas (called automated mobility districts [AMDs]), and travel time and wait time feedbacks affect mode choices. With rail service headways of 15?min, and 15 SAVs serving FMLM connections to and from each AMD, simulations predict that 3.7% of the person-trip-making will shift from driving alone to transit use in a 3?mi?×?6?mi central Austin area. During a 3-h morning peak, 30 SAVs serve about 10 person-trips each (to or from the stations), with 3.4?min average wait time for SAVs, and an average vehicle occupancy of 0.74 persons (per SAV mile-traveled), as a result of empty SAV driving between riders. Sensitivity analysis of transit headways (from 5 to 20?min) and fleet sizes (from 5 to 20 vehicles in each AMD) shows an increase in FMLM mode share with more frequent transit service and larger fleet size, but total travel time served as the biggest determinant in trip-makers’ mode share.

47 OTHER INSTRUMENTATION↗

SRF cavity instability detection with machine learning at CEBAF

During the operation of the Continuous Electron Beam Accelerator Facility (CEBAF), one or more unstable superconducting radio-frequency (SRF) cavities often cause beam loss trips while the unstable cavities themselves do not necessarily trip off. The present RF controls for the legacy cavities report at only 1 Hz, which is too slow to detectfast transient instabilities during these trip events. These challenges make the identification of an unstable cavity out of the hundreds installed at CEBAF a difficult and time-consuming task. To tackle these issues, a fast data acquisition system (DAQ) for the legacy SRF cavities has been developed, which records the sample at 5 kHz. An unsupervised learning framework has been developed to identify anomalous SRF cavity behavior. We will discuss the present status of the DAQ system and our framework, along with recent successes in detecting anomalous cavity behavior. Overall, our method offers a practical solution for identifying unstable SRF cavities, contributing to increased beam availability and machine reliability.

Accelerator Physics↗

High-dimensional Data-driven Energy optimization for Multi-Modal Transit Agencies (HD-EMMA) (Final Technical Report)

Public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO 2 emission annually. Electric vehicles (EVs) can have a much lower environmental impact than comparable internal combustion engine vehicles (ICEVs), especially in urban areas. Unfortunately, EVs are also much more expensive than ICEVs. As a result, many public transit agencies can afford only mixed fleets of transit vehicles, consisting of EVs, hybrids (HEVs), and ICEVs. Transit agencies that operate such mixed fleets of vehicles face a challenging optimization problem: these agencies need to decide which vehicles are assigned to serving which transit trips. Since the advantage of EVs over ICEVs varies depending on the route and time of day (e.g., the benefit of EVs is higher in slower traffic with frequent stops and lower on highways), the assignment can have a significant effect on energy use and, hence, environmental impact. Through this project, we have developed reference data about energy collections and constructed a set of machine learning models that can accurately predict the energy consumption for the whole fleet at the level of each trip. We have used these models to develop a scheduling and assignment strategy that can rotate the different vehicle types across the transit agencies’ routes. The optimization algorithm ensures that the vehicles are matched to trips considering weather patterns, expected congestion, and road gradients to minimize the overall energy usage. We list the key observations from our project for other practitioners below. Details are available in the report, and the list of source code and our publications are included in the appendix. 1. We have demonstrated the feasibility of collecting, merging and analyzing large volumes of high-resolution real-world telemetry data from a mixed vehicle fleet. To mitigate the inherent noise of the recorded GPS points, the team developed an algorithm that filters data and maps the points onto a street. The algorithm considers previous and subsequent location measurements and different characteristics of nearby streets to determine how likely the vehicle travels on them. Then, the team segmented the time series into disjoint contiguous samples based on adjacent road segments and repeated the outlier detection and removal. For each data point, the team added features corresponding to elevation changes within the samples, weather features, such as temperature, and traffic data, such as speed ratio between actual speed and free-flow speed. 2. We have developed two forms of machine learning models that be used to understand and analyze the energy operations of a mixed vehicle transit fleet. The micro prediction model provides estimates of instantaneous energy prediction for all types of buses (diesel, hybrid, and electric). Such a model is important in evaluating the energy impacts of real-time bus operation strategies, but it is challenging due to diversified driving cycles of transit buses. The model can help the drivers understand the impact of their driving behaviors and short-term congestions. The macro prediction models estimate average energy consumption across the whole trip considering the features: distance traveled, various road-type features, elevation change, day of the week, time of day, various weather features (temperature, humidity, etc.), and traffic features (speed ratio and jam factor). 3. We have demonstrated that it is possible to transfer the machine learning models we have developed in this project to other teams and cities by using inductive transfer learning. We also showed that the performance of the macro energy prediction models can be improved using a multi-task learning approach where the learning parameters are shared between the models being developed for different vehicle types. The advantage of this approach is improved learning performance as the models can exploit common spatio-temporal and environmental characteristics. 4. Finally, we have developed trip and vehicle assignment and scheduling algorithms that use the energy prediction models and develop a trip to vehicle type (diesel, electric, hybrid) assignment for the whole operation to reduce overall emissions and cost. We have shown through simulations that the proposed algorithms can save $\$$ 48,910 in energy costs and 175 metric tons of CO 2 emission annually for CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Space Flight Handbooks. Volume 3- Planetary Flight Handbook: Supplementary Trajectory Data: Venus to Earth and Mars to Earth - Part 2

Parts 2 and 3 present tabulations of trajectory data for scheduling flights to and from Venus and Mars during the period 1960-2000. Part 2 contains information for outbound flights to these planets; Part 3 contains information for trajectories returning from the planets to Earth. Each Part contains data for single-plane transfers, as well as for broken-plane transfers which employ a midcourse plane-change to eliminate the high speed "ridges." The mathematical analyses employed for all calculations are described in Part 1 of this handbook. To facilitate the construction of round-trip trajectories, the date at the target planet is held fixed while the trip duration is varied in 10-day increments from zero days to the length of that planet's synodic period with Earth. Dates of arrival at the target planet are presented in the extreme right-hand column of Part 2, and dates of departure from the target planet are presented in the extreme left-hand column of Part 3. Thus, by holding Part 2 directly to the left of Part 3, the analyst may easily and rapidly scan all trip possibilities which involve any desired stopover time at the target planet. Within approximately 200 days of each conjunction or opposition, data are presented in 10-day increments at the target planet. Only those trips are listed for which the hyperbolic excess speeds at either or both ends of the trajectory do not exceed 0.6 EMOS (Earth Mean Orbital Speed). For the remaining mission regions, the requirements are so smoothly varying that a 50-day interval in dates at the target planet may be employed; the 10-day interval in trip times is, however, preserved here. In these regions, only those trips are listed for which either or both speeds do not exceed 0.3 EMOS.

INTERPLANETARY FLIGHT↗

Crew factors in flight operations 6: Psychophysiological responses to helicopter operations

Thirty-two helicopter pilots were studied before, during, and after 4-5 day trips providing support services from Aberdeen, Scotland, to rigs in the North Sea oil fields. Early on-duty times obliged subjects to wake up 1.5 hours earlier on trip days than on pretrip days. Consequently, they slept nearly an hour less per night on trips. They reported more fatigue on post-trip days than on pretrip days, suggesting a cumulative effect of duty-related activities and sleep loss. Fatigue and negative affect were higher, and activation lower, by the end of trip days than by the end of pretrip days. The earlier a subject went on duty, the lower his activation by the end of the day. Caffeine consumption increased 42 percent on trip days. The incidence of headache doubled, of back pain increased twelve fold, and of burning eyes quadrupled. In the aircraft studied, thermal discomfort and high vibration levels were common. The longer pilots remained on duty, the more negative their mood became.

Gander, Philippa H.↗

Stability Analysis of Roughness Array Wake in a High-Speed Boundary Layer

Computations are performed to examine the effects of both an isolated and spanwise periodic array of trip elements on a high-speed laminar boundary layer, so as to identify the potential physical mechanisms underlying an earlier transition to turbulence as a result of the trip(s). In the context of a 0.333 scale model of the Hyper-X forebody configuration, the time accurate solution for an array of ramp shaped trips asymptotes to a stationary field at large times, indicating the likely absence of a strong absolute instability in the mildly separated flow due to the trips. A prominent feature of the wake flow behind the trip array corresponds to streamwise streaks that are further amplified in passing through the compression corner. Stability analysis of the streaks using a spatial, 2D eigenvalue approach reveals the potential for a strong convective instability that might explain the earlier onset of turbulence within the array wake. The dominant modes of streak instability are primarily sustained by the spanwise gradients associated with the streaks and lead to integrated logarithmic amplification factors (N factors) approaching 7 over the first ramp of the scaled Hyper-X forebody, and substantially higher over the second ramp. Additional computations are presented to shed further light on the effects of both trip geometry and the presence of a compression corner on the evolution of the streaks.

Choudhari, Meelan↗