Computer simulation study of bruceton and probit methods of sensitivity testing
Computer simulation study of Bruceton and Probit methods of sensitivity testing for launch vehicle explosion application
LAUNCH VEHICLE↗
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Multilevel Probit Regression for 3-Alternative Forced Choice Audibility Testing
A recent psychoacoustic test at NASA Langley generated a dataset of 3-alternative forced-choice responses for 40 subjects that measured the audibility of a tone complex in a shaped broadband masker. The task was completed by 4 subjects at a time in a small theatre-like environment using predetermined stimuli levels. These data were subject to 4 forms of probit regression: a “complete pooling” analysis in which all data from the test was fit with one curve, two forms of “no pooling” analyses in which subjects’ data were treated individually (using both packaged and custom software), and a “partial pooling” analysis in which multilevel-regression software fit both individual curves as well as population-level parameters at the same time. The results of the analyses are compared in terms of both individual- and population-level parameters. Partial pooling appears to give the most consistent results at both levels, as well as provide the most robustness among the packaged approaches (albeit with added complexity over single-level regression). These results are also contained in a recent NASA technical memorandum entitled “Comparisons of Analysis Methods Applied to Alternative Forced Choice Audibility Data.”
Psychoacoustics↗
Parametric and Nonparametric Models of U.S. Cost Overruns for Nuclear Power Plants
This study presents new data-driven models to estimate the effect of capacity on the percentage of cost overruns in the United States for nuclear power plant construction projects before and after the Three Mile Island accident. Parametric and nonparametric models have been developed that describe the significant shifts in nuclear energy costs during the dynamic environment. Employing a contemporary descriptive methodology and a quantitative analysis, we furnish a comprehensive overview of the alterations in cost overrun distribution and show the changes observed in other pivotal metrics alongside cost overruns. Our emphasis lies in documenting the fluctuations in cost overruns alongside nuclear reactor capacity levels and the increase of the overnight capital costs to build nuclear reactors. Our results show that increasing the size of nuclear reactors is not a factor statistically significant to decrease the percentage of cost overruns, and the probit model results provide evidence that an increase in size increases the probability of having cost overruns larger than 100% (double the estimated cost). We also compare our findings to two other regions: Asia and Europe.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Simultaneous global and local clustering in multiplex networks with covariate information
Understanding both global and layer-specific group structures is useful for uncovering complex patterns in networks with multiple interaction types. In this work, we introduce a new model, the hierarchical multiplex stochastic blockmodel, which simultaneously detects communities within individual layers of a multiplex network while inferring a global node clustering across the layers. A stochastic blockmodel is assumed in each layer, with probabilities of layer-level group memberships determined by a node’s global group assignment. Our model uses a Bayesian framework, employing a probit stick-breaking process to construct node-specific mixing proportions over a set of shared Griffiths–Engen–McCloseky distributions. These proportions determine layer-level community assignment, allowing for an unknown and varying number of groups across layers, while incorporating nodal covariate information to inform the global clustering. We propose a scalable variational inference procedure with parallelisable updates for application to large networks. Extensive simulation studies demonstrate our model’s ability to accurately recover both global and layer-level clusters in complicated settings, and applications to real data showcase the model’s effectiveness in uncovering interesting latent network structure.
community detection↗
New Norms or Old Habits: Evaluating Interlinked Trajectories of Online Shopping and Work Commute Post-Pandemic
The COVID-19 pandemic has significantly shifted travel behaviors, with major changes observed in online shopping and travel to work. Despite considerable research into pandemic-induced changes in travel behavior, it remains uncertain whether these new patterns have persisted or reverted to pre-pandemic norms. This study addresses this uncertainty by evaluating whether shifts in online shopping and work travel during the pandemic have become permanently ingrained in individuals' daily routine. Leveraging data from the 2022 National Household Travel Survey, a bivariate ordered probit model is employed to analyze changes in online shopping and work travel - whether they have increased, decreased, or remained stable compared to pre-pandemic levels across different population segments. The analysis finds that the pandemic did not significantly alter online shopping for home delivery and travel to work for the majority of society. However, a substantial portion of respondents reported increased online shopping for home delivery and reduced travel to work compared to pre-pandemic levels, with online shopping trends appearing more permanent. Segment-wise analysis and model results indicate heterogeneity in behavioral shifts with females engaging more in online shopping, while zero-vehicle households are traveling less to work, compared to pre-pandemic levels. Additionally, increase in online shopping frequency is significantly and negatively correlated with decrease in traveling to work. These findings highlight the need for improved digital infrastructure, flexible work policies, and integrated transportation solutions tailored to evolving demographic and socioeconomic needs in the post-pandemic era. Additionally, the study calls for integrating passenger and freight movement in a single framework rather than treating them in silos.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Risk estimates for CO exposure in man based on behavioral and physiological responses in rodents
An examination of animal response to CO is studied along with potential models for extrapolating animal test data to humans. The best models for extrapolating data were found to be the Probit and Weibull models.
Gross, M. K.↗
Hypobaric decompression prebreathe requirements and breathing environment
To reduce incidence of decompression sickness (DCS), prebreathing 100 percent oxygen to denitrogenate is required prior to hypobaric decompressions from a sea level pressure breathing environment to pressures lower than 350 mm Hg (20,000 ft; 6.8 psia). The tissue ratio (TR) of such exposures equals or exceeds 1.7; TR being the tissue nitrogen pressure prior to decompression divided by the total pressure after decompression (((0.781)(14.697))/6.758). Designing pressure suits capable of greater pressure differentials, lower TR's, and procedures which limit the potential for DCS occurrence would enhance operational efficiency. The current 10.2 psia stage decompression prior to extravehicular activity (EVA) from the Shuttle in the 100 percent oxygen, 4.3 psia suit, results in a TR of 1.65 and has proven to be relatively free of DCS. Our recent study of zero-prebreathe decompressions to 6.8 psia breathing 100 percent oxygen (TR = 1.66) also resulted in no DCS (N = 10). The level of severe, Spencer Grades 3 or 4, venous gas emboli (VGE) increased from 0 percent at 9.5 psia to 40 percent at 6.8 psia yielding a Probit curve of VGE risk for the 51 male subjects who participated in these recent studies. Earlier, analogous decompressions using a 50 percent oxygen, 50 percent nitrogen breathing mixture resulted in one case of DCS and significantly higher levels of severe VGE, e.g., at 7.8 psia, the mixed gas breathing environment resulted in a 56 percent incidence of severe VGE versus 10 percent with use of 100 percent oxygen. The report of this study recommended use of 100 percent oxygen during zero-prebreathe exposure to 6.8 psia if such a suit could be developed. For future, long-term missions, we suggest study of the effects of decompression over several days to a breathing environment of 150 mmHg O2 and approximately 52 mmHg He as a means of eliminating DCS and VGE hazards during subsequent excursions. Once physiologically adapted to a 4 psia vehicle, base, or space station segment, crew members could use greatly simplified EVA suits with greater mobility and no prebreathe requirement.
Webb, James T.↗
Initiation current measurements for hot bridgewire devices
One-shot type testing of hot bridgewire explosive cartridges provides the weakest possible firing characteristic data. One-shot type testing includes the Bruceton and the Probit methods, and all their off-shoots. One-shot testing is used for only one reason: the fear of 'dudding.' Modern programmable power supplies and oscilloscopes can now be used to obtain data with no fear of dudding. Any continued use of these old, one-shot type test methods is irresponsible behavior. Our society deserves better testing methods and will get them through the courts if we cannot make these changes on our own.
OBarr, Gerald L.↗
Parafoveal Target Detectability Reversal Predicted by Local Luminance and Contrast Gain Control
This project is part of a program to develop image discrimination models for the prediction of the detectability of objects in a range of backgrounds. We wanted to see if the models could predict parafoveal object detection as well as they predict detection in foveal vision. We also wanted to make our simplified models more general by local computation of luminance and contrast gain control. A signal image (0.78 x 0.17 deg) was made by subtracting a simulated airport runway scene background image (2.7 deg square) from the same scene containing an obstructing aircraft. Signal visibility contrast thresholds were measured in a fully crossed factorial design with three factors: eccentricity (0 deg or 4 deg), background (uniform or runway scene background), and fixed-pattern white noise contrast (0%, 5%, or 10%). Three experienced observers responded to three repetitions of 60 2IFC trials in each condition and thresholds were estimated by maximum likelihood probit analysis. In the fovea the average detection contrast threshold was 4 dB lower for the runway background than for the uniform background, but in the parafovea, the average threshold was 6 dB higher for the runway background than for the uniform background. This interaction was similar across the different noise levels and for all three observers. A likely reason for the runway background giving a lower threshold in the fovea is the low luminance near the signal in that scene. In our model, the local luminance computation is controlled by a spatial spread parameter. When this parameter and a corresponding parameter for the spatial spread of contrast gain were increased for the parafoveal predictions, the model predicts the interaction of background with eccentricity.
Ahumada, Albert J., Jr.↗
Focused Assessment with Sonography for Trauma in weightlessness: a feasibility study
BACKGROUND: The Focused Assessment with Sonography for Trauma (FAST) examines for fluid in gravitationally dependent regions. There is no prior experience with this technique in weightlessness, such as on the International Space Station, where sonography is currently the only diagnostic imaging tool. STUDY DESIGN: A ground-based (1 g) porcine model for sonography was developed. We examined both the feasibility and the comparative performance of the FAST examination in parabolic flight. Sonographic detection and fluid behavior were evaluated in four animals during alternating weightlessness (0 g) and hypergravity (1.8 g) periods. During flight, boluses of fluid were incrementally introduced into the peritoneal cavity. Standardized sonographic windows were recorded. Postflight, the video recordings were divided into 169 20-second segments for subsequent interpretation by 12 blinded ultrasonography experts. Reviewers first decided whether a video segment was of sufficient diagnostic quality to analyze (determinate). Determinate segments were then analyzed as containing or not containing fluid. A probit regression model compared the probability of a positive fluid diagnosis to actual fluid levels (0 to 500 mL) under both 0-g and 1.8-g conditions. RESULTS: The in-flight sonographers found real-time scanning and interpretation technically similar to that of terrestrial conditions, as long as restraint was maintained. On blinded review, 80% of the recorded ultrasound segments were considered determinate. The best sensitivity for diagnosis in 0 g was found to be from the subhepatic space, with probability of a positive fluid diagnosis ranging from 9% (no fluid) to 51% (500 mL fluid). CONCLUSIONS: The FAST examination is technically feasible in weightlessness, and merits operational consideration for clinical contingencies in space.
NASA Discipline Life Sciences Technologies↗
Pressure Flammability Thresholds in Oxygen of Selected Aerospace Materials
The experimental approach consisted of concentrating the testing in the flammability transition zone following the Bruceton Up-and-Down Method. For attribute data, the method has been shown to be very repeatable and most efficient. Other methods for characterization of critical levels (Karberand Probit) were also considered. The data yielded the upward limiting pressure index (ULPI), the pressure level where approx.50% of materials self-extinguish in a given environment.Parametric flammability thresholds other than oxygen concentration can be determined with the methodology proposed for evaluating the MOC when extinguishment occurs. In this case, a pressure threshold in 99.8% oxygen was determined with the methodology and found to be 0.4 to 0.9 psia for typical spacecraft materials. Correlation of flammability thresholds obtained with chemical, hot wire, and other ignition sources will be conducted to provide recommendations for using alternate ignition sources to evaluate flammability of aerospace materials.
Hirsch, David↗
Development of Head Injury Assessment Reference Values Based on NASA Injury Modeling
NASA is developing a new capsule-based, crewed vehicle that will land in the ocean, and the space agency desires to reduce the risk of injury from impact during these landings. Because landing impact occurs for each flight and the crew might need to perform egress tasks, current injury assessment reference values (IARV) were deemed insufficient. Because NASCAR occupant restraint systems are more effective than the systems used to determine the current IARVs and are similar to NASA s proposed restraint system, an analysis of NASCAR impacts was performed to develop new IARVs that may be more relevant to NASA s context of vehicle landing operations. Head IARVs associated with race car impacts were investigated by completing a detailed analysis of all of the 2002-2008 NASCAR impact data. Specific inclusion and exclusion criteria were used to select 4071 impacts from the 4015 recorder files provided (each file could contain multiple impact events). Of the 4071 accepted impacts, 274 were selected for numerical simulation using a custom NASCAR restraint system and Humanetics Hybrid-III 50th percentile numerical dummy model in LS-DYNA. Injury had occurred in 32 of the 274 selected impacts, and 27 of those injuries involved the head. A majority of the head injuries were mild concussions with or without brief loss of consciousness. The 242 non-injury impacts were randomly selected and representative of the range of crash dynamics present in the total set of 4071 impacts. Head dynamics data (head translational acceleration, translational change in velocity, rotational acceleration, rotational velocity, HIC-15, HIC-36, and the Head 3ms clip) were filtered according to SAE J211 specifications and then transformed to a log scale. The probability of head injury was estimated using a separate logistic regression analysis for each log-transformed predictor candidate. Using the log transformation constrains the estimated probability of injury to become negligible as IARVs approach zero. For the parameters head translational acceleration, head translational velocity change, head rotational acceleration, HIC-15, and HIC-36, conservative values (in the lower 95% confidence interval) that gave rise to a 5% risk of any injury occurring were estimated as 40.0 G, 7.9 m/s, 2200 rad/s2, 98.4, and 77.4 respectively. Because NASA is interested in the consequence of any particular injury on the ability of the crew to perform egress tasks, the head injuries that occurred in the NASCAR dataset were classified according to a NASA-developed scale (Classes I - III) for operationally relevant injuries, which classifies injuries on the basis of their operational significance. Additional analysis of the data was performed to determine the probability of each injury class occurring, and this was estimated using an ordered probit model. For head translational acceleration, head translational velocity change, head rotational acceleration, head rotational velocity, HIC-36, and head 3ms clip, conservative values of IARVs that produced a 5% risk of Class II injury were estimated as 50.7 G, 9.5 m/s, 2863 rad/s2, 11.0 rad/s, 30.3, and 46.4 G respectively. The results indicate that head IARVs developed from the NASCAR dataset may be useful to protect crews during landing impact.
Somers, Jeffrey T.↗
Multiclass Classification Using Bayesian Multivariate Adaptive Regression Splines
We present a new Bayesian model for the problem of multiclass classification. In this model, the probabilities of class membership of a given observation are determined by the mean of a latent Gaussian distribution. The mean functions of this latent distribution consist of combinations of highly flexible basis functions of the inputs: multivariate adaptive regression splines (MARS), first developed for multiple regression. We use reversible jump Markov chain Monte Carlo to make inference on the classification model, including the number of basis functions. We compare the probabilistic classification performance of our proposed approach to existing methods on simulated and benchmark data, and compare uncertainty estimates on simulated data. Our proposed method compares favorably with existing Bayesian and frequentist multiclass classification methods in out-of-sample probabilistic classification, and uncertainty estimation of these probabilistic classifications. We examine the fit of the proposed method to a data set of hurricane storm surge levels near Delaware Bay, US, and conclude that sea level rise is a key contributor to damage delivered by storm surge.
97 MATHEMATICS AND COMPUTING↗