Crew station research and development facility training for the light helicopter demonstration/validation program

The U.S. Army Crew Station Research and Development Branch (CSRDB) of the Aircraft Simulation Division (AVSCOM) was tasked by the Light Helicopter Program Manager (LH-PM) to provide training to Army personnel in advanced aircraft simulation technology. The purpose of this training was to prepare different groups of pilots to support and evaluate two contractor simulation efforts during the Demonstration/Validation (DEM/VAL) phase of the LH program. The personnel in the CSRDB developed mission oriented training programs to accomplish the objectives, conduct the programs, and provide guidance to army personnel and support personnel throughout the DEM/VAL phase

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty are rendered obsolete since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods.This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper shows how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components

Bubble Lift-off Size in Forced Convective Subcooled Boiling Flow

Forced convective subcooled boiling flow experiments were conducted in a BWR-scaled vertical upward annular channel. Water was used as the testing fluid, and the tests were performed at atmospheric pressure. A high-speed digital video camera was applied to capture the dynamics of the bubble nucleation process. Bubble lift-off diameters were obtained from the images for a total of 91 test conditions. A force balance analysis of a growing bubble was performed to predict the bubble lift-off size. The dimensionless form of the bubble lift-off diameter was formulated to be a function of Jacob number and Prandtl number. The proposed model agreed well with the experimental data within the averaged relative deviation of ±35.2 %

Comparison of Outcomes in Level I vs Level II Trauma Centers in Patients Undergoing Craniotomy or Craniectomy for Severe Traumatic Brain Injury.

BACKGROUND: Traumatic brain injury (TBI) carries a devastatingly high rate of morbidity and mortality. OBJECTIVE: To assess whether patients undergoing craniotomy/craniectomy for severe TBI fare better at level I than level II trauma centers in a mature trauma system. METHODS: The data were extracted from the Pennsylvania Trauma Outcome Study database. Inclusion criteria were patients \u3e 18 yr with severe TBI (Glasgow Coma Scale [GCS] score less than 9) undergoing craniotomy or craniectomy in the state of Pennsylvania from January 1, 2002 through September 30, 2017. RESULTS: Of 3980 patients, 2568 (64.5%) were treated at level I trauma centers and 1412 (35.5%) at level II centers. Baseline characteristics were similar between the 2 groups except for significantly worse GCS scores at admission in level I centers (P = .002). The rate of in-hospital mortality was 37.6% in level I centers vs 40.4% in level II centers (P = .08). Mean Functional Independence Measure (FIM) scores at discharge were significantly higher in level I (10.9 ± 5.5) than level II centers (9.8 ± 5.3; P \u3c .005). In multivariate analysis, treatment at level II trauma centers was significantly associated with in-hospital mortality (odds ratio, 1.2; 95% confidence interval, 1.03-1.37; P = .01) and worse FIM scores (odds ratio, 1.4; 95% confidence interval, 1.1-1.7; P = .001). Mean hospital and ICU length of stay were significantly longer in level I centers (P \u3c .005). CONCLUSION: This study showed superior functional outcomes and lower mortality rates in patients undergoing a neurosurgical procedure for severe TBI in level I trauma centers

In-situ velocity imaging of ultracold atoms using slow--light

The optical response of a moving medium suitably driven into a slow-light propagation regime strongly depends on its velocity. This effect can be used to devise a novel scheme for imaging ultraslow velocity fields. The scheme turns out to be particularly amenable to study in-situ the dynamics of collective and topological excitations of a trapped Bose-Einstein condensate. We illustrate the advantages of using slow-light imaging specifically for sloshing oscillations and bent vortices in a stirred condensate

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk, and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results, and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods, such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty, are rendered obsolete, since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods. This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper describes how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components

Developments in an HF Nowcasting Model for Trans-Polar Airline Routes

HF communications can be difficult in the polar regions since they are strongly influenced by space weather events. Airline communications within the polar regions rely on HF communications and improved nowcasting and forecasting techniques in support of this are now required. Previous work has demonstrated that ray tracing through a realistic, historical ionosphere provides signal coverage in good agreement with measurements. This paper presents an approach to providing a real-time ionospheric model by assimilating TEC measurements and validates it against observations from ionosondes