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The deployment of Li-ion batteries covers a wide range of energy storage applications, from mobile phones, e-bikes, electric vehicles (EV) and stationary energy storage systems. However, safety issue such as thermal runaway is always one of the most important concerns to prevent Li-ion batteries from further market penetration. A standardized single-side indentation test protocol was developed to mechanically induce an internal short-circuit. The cell voltage, compressive load, indenter stroke, and temperature at the indentation point are measured in time series. The test data of each cell, along with cell parameters such as dimensions, mass, chemistry, state of charge (SOC), capacity, are integrated together to calculate a thermal runaway severity score from 0 to100. Complete data collection process including the original measured record, test method, severity score calculation scheme is presented in this article. The thermal runaway severity analysis and the more than 100 tested Li-ion battery records provide a good data source for further comparison and ranking of thermal runaway risks.
The Ocean Health Index measured Ecological Integrity as the relative condition of assessed species in a given location. This was calculated as the weighted sum of the International Union for Conservation of Natures (IUCN) assessments of species. Weights used were based on the level of extinction risk following Butchart et al.2007: EX (extinct) 0.0, CR (critically endangered) 0.2, EN (endangered) 0.5, VU (vulnerable) 0.7, NT (not threatened) 0.9, and LC (least concern) 0.99. For primarily coastal goals, the spatial average of these per pixel scores was based on a 3nmi buffer; for goals derived from all ocean waters, the spatial average was computed for the entire EEZ.
This slide presentation reviews the Integrated Medical Model (IMM) database, which is an organized evidence base for assessing in-flight crew health risk. The database is a relational database accessible to many people. The database quantifies the model inputs by a ranking based on the highest value of the data as Level of Evidence (LOE) and the quality of evidence (QOE) score that provides an assessment of the evidence base for each medical condition. The IMM evidence base has already been able to provide invaluable information for designers, and for other uses.
The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.
The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.
A coronary heart disease index was developed from longitudinal ECG (LCG) tracings to serve as a cardiac health measure in studies of working and, essentially, asymptomatic populations, such as pilots and executives. For a given subject, the index consisted of a composite score based on the presence of LCG aberrations and weighted values previously assigned to them. The index was validated by correlating it with the known presence or absence of CHD as determined by a complete physical examination, including treadmill, resting ECG, and risk factor information. The validating sample consisted of 111 subjects drawn by a stratified-random procedure from 5000 available case histories. The CHD index was found to be significantly more valid as a sole indicator of CHD than the LCG without the use of the index. The index consistently produced higher validity coefficients in identifying CHD than did treadmill testing, resting ECG, or risk factor analysis.
High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing RAZ scoring is a simple, accurate and inexpensive screening technique for cardiomyopathy. Although HF QRS ECG is highly sensitive for cardiomyopathy, its specificity may be compromised in patients with cardiac pathologies other than cardiomyopathy, such as uncomplicated coronary artery disease or multiple coronary disease risk factors. Further studies are required to determine whether HF QRS might be useful for monitoring cardiomyopathy severity or the efficacy of therapy in a longitudinal fashion.
The large-scale deployment of Li-ion batteries in stationary energy storage and electrical vehicle applications demands a strong focus on safety, particularly on the thermal runaway risk and severity evaluation. A standardized single-side mechanical indentation test protocol was developed to induce an internal short-circuit (ISC) and evaluate cells' thermal runaway severity at different state of charge (SOC). The observed hazard severity (OHS in five categories) and evaluated scores in this work have a comprehensive consideration of each cell's capacity, initial voltage, SOC, temperature and voltage change, allowing a better evaluation of the cells' thermal runaway potential. This method was applied to about 200 Li-ion batteries in order to build an extensive thermal runaway database covering various SOCs, capacities and chemistries. In this study, we monitored the transitions of stored electrochemical energy and applied mechanical energy into both thermal energy and acoustic emissions (AE). The surface temperature and mechanical failures were monitored by infrared imaging and AE to capture critical events within battery cells throughout the mechanical indentation tests. Furthermore, the initial temperature maps can predict two types of follow-up events: thermal runaway or gradual heat release via conduction. Analyzing each cell's severity, AEs, and leveraging the evolving database offer insights into predicting occurrences of thermal runaway. The test method, thermal runaway severity evaluation and prediction, and the corresponding database provide battery designers, manufacturers, and end-users a clear overview of Li-ion batteries' thermal runaway potential under mechanical abuse, advancing the safety design of Li-ion batteries.
The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting mass and volume constraints.
The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting mass and volume constraints.
New NASA launch vehicles will require development of robust systems in a fiscally-constrained environment. NASA, Department of Defense (DoD), and commercial space companies routinely conduct ground vibration tests as an essential part of math model validation and launch vehicle certification. Although ground vibration testing must be a part of the integrated test planning process, more affordable approaches must also be considered. A study evaluated several ground vibration test options for the NASA Constellation Program flight test vehicles, Orion-1 and Orion-2, which concluded that more affordable ground vibration test options are available. The motivation for ground vibration testing is supported by historical examples from NASA and DoD. The approach used in the present study employed surveys of ground vibration test subject-matter experts that provided data to qualitatively rank six test options. Twenty-five experts from NASA, DoD, and industry provided scoring and comments for this study. The current study determined that both element-level modal tests and integrated vehicle modal tests have technical merits. Both have been successful in validating structural dynamic math models of launch vehicles. However, element-level testing has less overall cost and schedule risk as compared to integrated vehicle testing. Future NASA launch vehicle development programs should anticipate that some structural dynamics testing will be necessary. Analysis alone will be inadequate to certify a crew-capable launch vehicle. At a minimum, component and element structural dynamic tests are recommended for new vehicle elements. Three viable structural dynamic test options were identified. Modal testing of the new vehicle elements and an integrated vehicle test on the mobile launcher provided the optimal trade between technical, cost, and schedule.
Travel and tourism is one of the world's largest businesses. Its gross revenues exceed $400 billion per year in the U.S. alone, and it is our second largest employer. U.S. private sector business revenues in the space information area now approximate $10 billion per year, and are increasing rapidly. Not so in the human spaceflight area. After spending $100s of billions (1998 dollars) in public funds thereon, and continuing to spend over $5 billion per year, the government is still the only customer for human spaceflight goods and services. Serious and detailed consideration was first given to the possibility of space being opened up to trips by the general public three decades ago, and some initial attempts to do so were made a dozen years ago. But the difficulties were great and the Challenger disaster put an end to them. In recent years professional space tourism studies have been conducted in the United Kingdom, Germany and, especially, Japan. In the U.S., technological progress has been pronounced; we have had nearly a decade's experience in seeing our astronauts travel to-from low Earth orbit (LEO) safely, and we expect to commence assembly of a LEO space station housing a half-dozen people this year. Too, NASA and our space industry now have new and promising space transportation development programs underway, especially the X-33 and X-34 programs, and some related, further generation, basic technology development programs. And five private companies are also working on the design of new surface - LEO vehicles. The first professional space tourism market studies have been conducted in several countries in the past few years, especially in Japan and here. The U.S. study makes it clear that, conceptually, tens of millions of us would like to take a trip to space if we could do so with reasonable safety, comfort and reliability, and at an acceptable price. Initial businesses will address the desires of those willing to pay a greater price and accept a greater risk. A two-year cooperative Space Act agreement study has been conducted by our National Aeronautics and Space Administration and the Space Transportation Association. It was conducted by NASA and STA study leaders drawing upon the competence, experience and hard-nosed imagination of a national Steering Group and scores of attendees at a multi-day Workshop. The study has involved scores of professionals and business people from various areas: astronauts; space booster technology and operations professionals; a hotel architect and a hotel operator; an airline planner; insurance underwriters; space sickness experts; space theme park designers; space and travel and tourism association and business executives; a space-related financier; university tourism and space policy experts; present and former space-responsible government officials; space entrepreneurs; space writers; This study concludes that serious national attention should now be given to activities that would enable the expansion of today's terrestrial space tourism businesses, and the creation of in-space travel and tourism businesses. Indeed, it concludes that, in time, it should become a very important part of our Country's overall commercial and civil space business-program structure.
After they return to Earth, astronauts experience sensorimotor disturbances that disrupt their ability to walk. We have previously shown that training with a variety of sensorimotor adaptive challenges enhances the capability of adapting to novel sensorimotor conditions. We are currently developing a sensorimotor adaptability (SA) training program designed to facilitate recovery of function after gravitational transitions. The purpose of this study was to determine whether trained subjects could transfer learned skills from one discordant visuo-proprioceptive environment to another. During three sessions, subjects walked at 2.5 km/h on a treadmill mounted on a motion base platform. Ten subjects trained with a combination of lateral treadmill translation and superimposed sinusoidal lateral optic flow that was presented on a large screen positioned in front of them. Ten controls completed the same training schedule while viewing only the forward optic flow with no visual or physical oscillation. Twenty minutes after the final training session, all subjects completed a 2-minute trial with a novel combination of visual and treadmill roll perturbations not previously experienced during the training (Transfer Test). Compared to the untrained group, participants who received SA training showed faster reaction times and, based on a composite score derived from stride frequency, heart rate, and reaction time, an overall enhanced performance. Our results showed that an SA training program can improve overall walking performance when subjects are exposed to novel incongruent sensory environments. This training has application for both enhancing adaptive responses in astronauts and reducing fall and injury risk in the elderly.
Growing fresh, nutritious, palatable produce for crew consumption during spaceflight may provide health-promoting, bioavailable nutrients and enhance the astronaut dietary experience as we move toward longer-duration missions. Tending plants may also serve as a countermeasure for crew psychological stresses associated with spaceflight. However, requirements to support consistent growth of a variety of nutritious crops under spaceflight environmental conditions remain unclear. This study explores the potential to grow crops for consumption on the International Space Station (ISS) using the Veggie vegetable-production system. VEG-04A and B were two flight tests conducted in 2019 with the leafy green crop Mizuna mustard. Mizuna was grown in two Veggie chambers simultaneously, with the chambers set to different red-to-blue light formulations; one Veggie was programmed as “red-rich” and the second as “blue-rich.” Light quality is known to impact plant growth, nutrition, microbiology, and organoleptic characteristics on Earth, and the Veggie flight tests examined how these impacts might differ in microgravity. VEG-04A was a 35-day growth test with a single harvest. VEG-04B, a 58-day test with harvests at four, six, and eight weeks from the same plants, assessed sustained productivity. Challenges with the watering program occurred early during VEG-04A, and several plants failed to survive in both the flight and ground control operations. Thus, prior to VEG-04B, an extra test was conducted to tailor water timing and volumes. This test allowed a fine tuning of methods for VEG-04B, and generally plant survival was better in that experiment. At each harvest, the astronauts froze half of the edible plant tissue to return to Earth and weighed the remaining half using the ISS Mass Measurement Device (MMD). Weighed samples were then cleaned with produce-sanitizing wipes, and consenting crew members participated in organoleptic evaluation of the fresh produce. Organoleptic evaluations were conducted on the Mizuna crops grown in both light treatments, and data from these tests are compared to ground data collected at JSC. The remaining sanitized produce was available for crew consumption as desired. Frozen flight samples were returned for microbial and chemical analyses to assess food safety and nutritional quality. Microbial assessments included culturing and identifying aerobic bacteria, yeasts, and molds, and screening for specific human pathogens. Chemical nutrient analyses included assessing elements, antioxidants, and phenolics in plant tissues. Crew members involved in plant operations completed behavioral health surveys pre-flight, in-flight associated with plant growth and harvest activities, and post-flight. Surveys captured the amount of time spent on different plant-related operations, enjoyment of the different activities, engagement with Veggie, experience interacting with Veggie, and sensory stimulation associated with growing plants in Veggie. Within each study, plant growth did not differ across light treatment or location (flight versus ground). In general, more biomass was produced in most treatments during the longer study, but growth of this crop declined over time with the repeated harvests. On average, bacterial and fungal counts were significantly lower on ground control samples than flight samples, and microbial counts increased with repeated harvests. Light treatment did not influence any elements in tissues tested; however, the growth duration did impact levels of several elements. Organoleptic scores were generally higher in flight, and ground tasters considered samples more bitter. Amount of interaction and responses to Veggie varied widely by individual. Enjoyable tasks had higher impact than non-enjoyable tasks and interacting with Veggie was generally viewed as positive. These tests on ISS are helping to mitigate the risk of an inadequate food supply for long-duration missions by adding fresh vegetables and key nutrients to the crew diet, and indicating which plant care activities are providing behavioral health benefits for the crew. This research was co-funded by the Human Research Program and Space Biology (MTL#1075) in the ILSRA 2015 NRA call. Videos due Jan. 25th.
Heavy-duty commercial vehicles present unique safety challenges due to their size, articulation dynamics, and operational complexity. As Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) become more common in Class 8 tractor-trailers, traditional crash-based metrics are no longer sufficient to evaluate safety performance. This study introduces the Near-Miss Safety Score (NMSS)—a quantitative, physics-informed framework developed as a leading indicator of safety for advanced commercial vehicle technologies. NMSS quantifies how close a vehicle or operator comes to a collision or safety-critical event by integrating vehicle kinematics (relative distance, velocity, and acceleration) with driver or system response latency and time-to-collision. A modifier function adjusts the base score for vehicle-specific and environmental factors such as trailer articulation, load distribution, braking condition, and roadway environment. The framework enables systematic evaluation of ADAS/ADS performance under a range of operational and degraded conditions. By capturing near-miss dynamics rather than relying on crash data, NMSS provides a proactive approach to risk assessment, accelerates technology validation, and enhances interpretability for regulators and fleet operators. The proposed NMSS was validated using data collected from a motorcoach platform, demonstrating the framework’s applicability to heavy-duty safety evaluation and performance benchmarking. Results and key insights are presented in this paper.
NASA's highly successful Kepler Mission has revolutionized our understanding of the Galaxy. We now know that planets, even Earth-size planets in the habitable zone, are common. With the end of the Kepler Mission we now look to the future with the Transiting Exoplanet Survey Satellite (TESS) which will discover thousands of exoplanets in orbit around the brightest stars in the sky. In a two-year survey, TESS will perform an all-sky search of more than 200,000 stars for temporary drops in brightness caused by planetary transits. With Kepler and TESS, humanity is finally at the verge of studying the masses, sizes, densities, orbits, and atmospheres of a large cohort of small planets, including a sample of rocky worlds in the habitable zones of their host stars which may prove to host life. The massive data sets generated by Kepler and TESS must be meticulously combed for the weakest planetary signals every month. While a daunting and error-prone task for humans, this is an exciting opportunity for the breakthroughs recently seen in machine learning. Specifically, traditional methods for identifying planet transits require extensive data processing pipelines followed by extensive human vetting. This manual process risks loss of information due to the data processing and to inconsistency and biases due to individual human vetters. The latest advancements in machine learning will allow an objective classifier to minimize the losses of information and greatly lessen the burden on the human vetters, in addition to providing assessment of quality and score to each planet candidate, freeing the humans to concentrate on border cases and other more interesting investigations.
We synthesize five complementary tropical cyclone (TC) hazard frameworks—RAFT (physics-based machine learning), CHAZ and MIT (statistical–dynamical), STORM (fully statistical), and CLIMADA (observation-driven resampling)—to characterize uncertainty in wind-related TC metrics relevant to energy applications. All datasets and the IBTrACS observational record are harmonized to a common 6-hourly, 2.5° grid. We compare basin-wide and coastal properties using consistent definitions for TC frequency, mean and maximum intensity, 24-hour intensification, and 6-hour translation speed, and quantify agreement with Pearson r, RMSE, and Kling–Gupta efficiency (KGE) alongside resampling-based confidence intervals. CLIMADA is included for basin context but excluded from coastal skill scoring because it resamples historical IBTrACS; if supplied with projected future tracks from an external hazard model, CLIMADA can be used to simulate future TC scenarios. Results show robust, cross-model signals: (i) a corridor of activity from the tropical Atlantic through the Caribbean into the Bahamas and western subtropical Atlantic; (ii) a meridional dipole in 24-hour intensification (low-latitude strengthening, subtropical weakening); and (iii) a transition from slower tropical motion to faster midlatitude translation. Coastal winds (mean and maximum) consistently cluster from the eastern Gulf into the Bahamas–western Atlantic transition. The largest structural spread occurs in the amplitude and footprint of lifetime maximum intensity and, secondarily, in translation speed; intensification exhibits similar central behavior across frameworks with variability in extremes. Translation speed shows the most uniform coastal agreement. These findings provide a decision envelope for wind-focused risk screening and clarify where uncertainty should be carried forward; wind-only results represent a lower bound on total hazard, motivating integration of surge and rainfall modules and a companion, asset-level damage analysis.