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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2018

Development of a Ground Test and Analysis Protocol for NASA's NextSTEP Phase 2 Habitation Concepts

The NASA Next Space Technologies for Exploration Partnerships (NextSTEP) program is a public-private partnership model that seeks commercial development of deep space exploration capabilities to support human spaceflight missions around and beyond cislunar space. NASA first issued the Phase 1 NextSTEP Broad Agency Announcement to U.S. industries in 2014, which called for innovative cislunar habitation concepts that leveraged commercialization plans for low-Earth orbit. These habitats will be part of the Deep Space Gateway (DSG), the cislunar space station planned by NASA for construction in the 2020s. In 2016, Phase 2 of the NextSTEP program selected five commercial partners to develop ground prototypes. A team of NASA research engineers and subject matter experts (SMEs) have been tasked with developing the ground-test protocol that will serve as the primary means by which these Phase 2 prototypes will be evaluated. Since 2008, this core test team has successfully conducted multiple spaceflight analog mission evaluations utilizing a consistent set of operational tools, methods, and metrics to enable the iterative development, testing, analysis, and validation of evolving exploration architectures, operations concepts, and vehicle designs. The purpose of implementing a similar evaluation process for the Phase 2 Habitation Concepts is to consistently evaluate different commercial partner ground prototypes to provide data-driven, actionable recommendations for Phase 3. This paper describes the process by which the ground test protocol was developed and the objectives, methods, and metrics by which the NextSTEP Phase 2 Habitation Concepts will be rigorously and systematically evaluated. The protocol has been developed using both a top-down and bottom-up approach. Top-down development began with the Human Exploration and Operations Mission Directorate (HEOMD) exploration objectives and ISS Exploration Capability Study Team (IECST) candidate flight objectives. Strategic questions and associated rationales, derived from these candidate architectural objectives, provide the framework by which the ground-test protocol will address the DSG stack elements and configurations, systems and subsystems, and habitation, science, and EVA functions. From these strategic questions, high-level functional requirements for the DSG were drafted and associated ground-test objectives and analysis protocols were established. Bottom-up development incorporated objectives from NASA SMEs in autonomy, avionics and software, communication, environmental control and life support systems, exercise, extravehicular activity, exploration medical operations, guidance navigation and control, human factors and behavioral performance, human factors and habitability, logistics, Mission Control Center operations, power, radiation, robotics, safety and mission assurance, science, simulation, structures, thermal, trash management, and vehicle health. Top-down and bottom-up objectives were integrated to form overall functional requirements - ground-test objectives and analysis mapping. From this mapping, ground-test objectives were organized into those that will be evaluated through inspection, demonstration, analysis, subsystem standalone testing, and human-in-the-loop (HITL) testing. For the HITL tests, mission-like timelines, procedures, and flight rules have been developed to directly meet ground test objectives and evaluate specific functional requirements. Data collected from these assessments will be analyzed to determine the acceptability of habitation element configurations and the combinations of capabilities that will result in the best habitation platform to be recommended by the test team for Phase 3.

Gernhardt, Michael L.↗
NASA NTRS2005

Optimal Sensor Selection for Health Monitoring Systems

Sensor data are the basis for performance and health assessment of most complex systems. Careful selection and implementation of sensors is critical to enable high fidelity system health assessment. A model-based procedure that systematically selects an optimal sensor suite for overall health assessment of a designated host system is described. This procedure, termed the Systematic Sensor Selection Strategy (S4), was developed at NASA John H. Glenn Research Center in order to enhance design phase planning and preparations for in-space propulsion health management systems (HMS). Information and capabilities required to utilize the S4 approach in support of design phase development of robust health diagnostics are outlined. A merit metric that quantifies diagnostic performance and overall risk reduction potential of individual sensor suites is introduced. The conceptual foundation for this merit metric is presented and the algorithmic organization of the S4 optimization process is described. Representative results from S4 analyses of a boost stage rocket engine previously under development as part of NASA's Next Generation Launch Technology (NGLT) program are presented.

Santi, L. Michael↗
NASA NTRS2009

First International Diagnosis Competition - DXC'09

A framework to compare and evaluate diagnosis algorithms (DAs) has been created jointly by NASA Ames Research Center and PARC. In this paper, we present the first concrete implementation of this framework as a competition called DXC 09. The goal of this competition was to evaluate and compare DAs in a common platform and to determine a winner based on diagnosis results. 12 DAs (model-based and otherwise) competed in this first year of the competition in 3 tracks that included industrial and synthetic systems. Specifically, the participants provided algorithms that communicated with the run-time architecture to receive scenario data and return diagnostic results. These algorithms were run on extended scenario data sets (different from sample set) to compute a set of pre-defined metrics. A ranking scheme based on weighted metrics was used to declare winners. This paper presents the systems used in DXC 09, description of faults and data sets, a listing of participating DAs, the metrics and results computed from running the DAs, and a superficial analysis of the results.

Kurtoglu, tolga↗
NASA NTRSDate not supplied

Performance Risk Model (PRisM) Proof-of-Concept: An Operational Decision Support Tool to Predict Crew Performance in Space from Available Performance Tests

The Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) team at NASA Glenn Research Center has developed a range of tools to evaluate astronaut health during spaceflight and to optimize the medical set required for missions. Among these, the Performance Risk Model (PRisM) represents a novel advancement, extending CHP-PRA’s focus beyond medical systems into the domain of human performance. Such tool could be pivotal in optimizing astronaut capabilities during space travel, thereby enhancing overall mission success. PRisM leverages data from well-established performance assessments conducted during previous crewed space missions and Earth analogs to strategically predict outcomes for planned tasks, even when direct performance testing has not been conducted for those specific tasks. To evaluate performance, PRisM references the various metrics outlined in NASA-STD-3001 and employs a methodology to integrate different performance scales. This framework analyzes the contribution of various human system task categories (HSTCs) to task execution and compares these contributions to the HSTCs’ involvement in other known tests. The model further employs a Monte Carlo simulation to sample performance scores from their distribution in operationally relevant tests such as those in Mulavara et al. (2018) and, by leveraging similarities in HSTC involvement, transfers this knowledge to actual mission tasks, such as those outlined in the "Human Exploration of Mars: Preliminary List of Crew Tasks”. The current PRisM proof-of-concept includes analyses of the impact of exercise and specific medications on astronauts’ performance, with provisions to incorporate additional countermeasures as data becomes available. Furthermore, the tool is customizable to include any system necessary to fully encompass the domain of human systems and can be adapted to evaluate performance for any spaceflight activities as requested by operational stakeholders. PRisM has the potential to assist the Human Research Program in exploring the capabilities trade space for optimized crew performance.

performance modeling↗
NASA NTRS2004

Science Goal Monitor: Science Goal Driven Automation for NASA Missions

Infusion of automation technologies into NASA s future missions will be essential because of the need to: (1) effectively handle an exponentially increasing volume of scientific data, (2) successfully meet dynamic, opportunistic scientific goals and objectives, and (3) substantially reduce mission operations staff and costs. While much effort has gone into automating routine spacecraft operations to reduce human workload and hence costs, applying intelligent automation to the science side, i.e., science data acquisition, data analysis and reactions to that data analysis in a timely and still scientifically valid manner, has been relatively under-emphasized. In order to introduce science driven automation in missions, we must be able to: capture and interpret the science goals of observing programs, represent those goals in machine interpretable language; and allow spacecrafts onboard systems to autonomously react to the scientist's goals. In short, we must teach our platforms to dynamically understand, recognize, and react to the scientists goals. The Science Goal Monitor (SGM) project at NASA Goddard Space Flight Center is a prototype software tool being developed to determine the best strategies for implementing science goal driven automation in missions. The tools being developed in SGM improve the ability to monitor and react to the changing status of scientific events. The SGM system enables scientists to specify what to look for and how to react in descriptive rather than technical terms. The system monitors streams of science data to identify occurrences of key events previously specified by the scientist. When an event occurs, the system autonomously coordinates the execution of the scientist s desired reactions. Through SGM, we will improve om understanding about the capabilities needed onboard for success, develop metrics to understand the potential increase in science returns, and develop an operational prototype so that the perceived risks associated with increased use of automation can be reduced.

Koratkar, Anuradha↗
NASA NTRS2006

A Comparison of Visual Statistics for the Image Enhancement of FORESITE Aerial Images with Those of Major Image Classes

Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally with the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging--terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

Johnson, Daniel J.↗
NASA NTRS2012

Community Coordinated Modeling Center: Addressing Needs of Operational Space Weather Forecasting

Models are key elements of space weather forecasting. The Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) hosts a broad range of state-of-the-art space weather models and enables access to complex models through an unmatched automated web-based runs-on-request system. Model output comparisons with observational data carried out by a large number of CCMC users open an unprecedented mechanism for extensive model testing and broad community feedback on model performance. The CCMC also evaluates model's prediction ability as an unbiased broker and supports operational model selections. The CCMC is organizing and leading a series of community-wide projects aiming to evaluate the current state of space weather modeling, to address challenges of model-data comparisons, and to define metrics for various user s needs and requirements. Many of CCMC models are continuously running in real-time. Over the years the CCMC acquired the unique experience in developing and maintaining real-time systems. CCMC staff expertise and trusted relations with model owners enable to keep up to date with rapid advances in model development. The information gleaned from the real-time calculations is tailored to specific mission needs. Model forecasts combined with data streams from NASA and other missions are integrated into an innovative configurable data analysis and dissemination system (http://iswa.gsfc.nasa.gov) that is accessible world-wide. The talk will review the latest progress and discuss opportunities for addressing operational space weather needs in innovative and collaborative ways.

Kuznetsova, M.↗
NASA NTRSDate not supplied

Loss of Control Detection for Commercial Transport Aircraft Using Conditional Variational Autoencoders

This work describes a detector for the loss of control condition of a commercial transport in flight. The detector has a belief state defined by the latent variable stochastic modeling of a conditional variational autoencoder (CVAE) constructed with bidirectional recurrent layers. In 2000, the Boeing Company and the NASA Langley Research Center jointly developed a quantitative set of metrics for defining loss-of-control (LOC) for a commercial transport. We use the thresholds for these quantitative metrics to define a condition vector for training the CVAE. First, we demonstrate through experimentation that reconstruction probability is an accurate indicator that the vehicle has shifted to an LOC state. Second, we introduce a technique for inferring that the vehicle is approaching a flight state change by measuring a shift in the sampling distributions of the CVAE latent space. The sampling distributions for flight observations that are approaching envelope limits are localized to external areas of the latent space. We provide an analysis of its applicability to flight data from NASA’s dynamically-scaled generic transport model (GTM) aircraft.

Loss of control↗
NASA NTRS2012

The NASA Heliophysics Active Final Archive at the Space Physics Data Facility

The 2009 NASA Heliophysics Science Data Management Policy re-defined and extended the responsibilities of the Space Physics Data Facility (SPDF) project. Building on SPDF's established capabilities, the new policy assigned the role of active "Final Archive" for non-solar NASA Heliophysics data to SPDF. The policy also recognized and formalized the responsibilities of SPDF as a source for critical infrastructure services such as VSPO to the overall Heliophysics Data Environment (HpDE) and as a Center of Excellence for existing SPDF science-enabling services and software including CDAWeb, SSCWeb/4D Orbit Viewer, OMNIweb and CDF. We will focus this talk to the principles, strategies and planned SPDF architecture to effectively and efficiently perform these roles, with special emphasis on how SPDF will ensure the long-term preservation and ongoing online community access to all the data entrusted to SPDF. We will layout our archival philosophy and what we are advocating in our work with NASA missions both current and future, with potential providers of NASA and NASA-relevant archival data, and to make the data and metadata held by SPDF accessible to other systems and services within the overall HpOE. We will also briefly review our current services, their metrics and our current plans and priorities for their evolution.

McGuire, Robert E.↗
NASA NTRS2023

Assessing Flow Formability of Aerospace Aluminum Alloys via DIC Tensile Testing

Over the past decade, NASA Langley Research Center (LaRC) has championed integrally stiffened cylinder (ISC) technology for single-piece, cryogenic tank barrels on launch vehicles. The current investigation aims to extend the hybrid spin/shear/flow forming process to aircraft fuselage structures, a damage tolerance critical application. The WF Maschinenbau VUD-600® vertical spin/flow forming facility recently established at LaRC represents a reasonable sub-scale facsimile of the ISC deformation process for research and development (R&D) purposes. The objective of this study is to explore whether tensile testing with digital image correlation (DIC) is an effective way to rank the formability of candidate aerospace Al alloys and expedite empirical forming trials. Specific tensile data, such as reduction of area, strain hardening exponent, and modulus of resilience, are used as formability metrics for a variety of alloy/temper/product form combinations. Results from high-strength aluminum alloys AA 2139, AA 2050, AA 2043 and AA 2219 are compared with the medium-strength, highly formable AA 6061 benchmark. Rolled, forged and cast preform materials in both the -O temper (fully annealed) and -T4 temper (solution-treated, quenched, and naturally aged) conditions are evaluated. AA 2139 plate in the -T4 temper emerges as the top-ranked material, based on the criteria selected. Starting with preforms in the -T4 temper will result in flow-formed material exhibiting mechanical properties closer to aircraft fuselage requirements. The optimum balance between strength and damage tolerance may also be achieved via post-forming procedures that avoid quenching and stretching.

Aluminum alloys↗
NASA NTRSDate not supplied

Modal Test and Model Correlation of NASA Plum Brook Station Mechanical Vibration Facility Head Expander –Lessons Learned from the Perspective of an Early-Career Engineer

In preparation for the Sierra Nevada Corporation’s (SNC) Dream Chaser spacecraft vibration test campaign at the Mechanical Vibration Facility (MVF) at NASA Plum Brook Station (PBS) in Sandusky, Ohio, a test-verified model of MVF is needed in order to be able to perform accurate pretest analysis used for determining response limits and abort levels. MVF was designed to vibration test MPCV Orion and was used to perform the system level vibration test of the European Service Module Structural Test Article (E-STA) in 2016. MVF is comprised of an 18 ft diameter annulus table that is driven with sixteen hydraulic vertical actuator assemblies and four hydraulic horizontal actuator assemblies, which allow it to perform single axis vibration testing in the vertical axis and in each of the two orthogonal horizontal axes without the need for reconfiguring the test article. A head expander for the MVF Table has been designed and built that fills in the center opening providing a continuous flat mounting surface with a maximum diameter of 16.25feet that expands the vibration testing capabilities of MVF. The MVF Table with this head expander will be used during the SNC Dream Chaser spacecraft vibration test campaign. Therefore, a critical element in a test-verified model of the MVF will be a test correlated finite element model (FEM) of the head expander. To obtain this, engineers from the Structural Dynamics Lab (SDL) at NASA Glenn Research Center (GRC) in Cleveland, Ohio performed a modal pretest analysis, conducted a modal test in July 2019, and most recently correlated the head expander finite element model to the modal test data up to 300 Hz. From the initial test preparations to the final delivery of a correlated finite element model, all efforts mentioned were led by the same early-career engineers at NASA GRC. From the viewpoint of an early-career engineer, lessons learned about modal pretest analysis, modal testing, and finite element model correlation of the MVF Table expander head will be presented and discussed. This will include the importance of understanding the limitations of using uncorrelated finite element models in the modal pretest analysis and planning, the importance of orthogonality metrics in judging adequacy and accuracy of test mode shapes, and the importance of having the FEM match the as built hardware in the model correlation effort.

Emma L Pierson↗
NASA NTRS2010

Pixel-Level Calibration in the Kepler Science Operations Center Pipeline

We present an overview of the pixel-level calibration of flight data from the Kepler Mission performed within the Kepler Science Operations Center Science Processing Pipeline. This article describes the calibration (CAL) module, which operates on original spacecraft data to remove instrument effects and other artifacts that pollute the data. Traditional CCD data reduction is performed (removal of instrument/detector effects such as bias and dark current), in addition to pixel-level calibration (correcting for cosmic rays and variations in pixel sensitivity), Kepler-specific corrections (removing smear signals which result from the lack of a shutter on the photometer and correcting for distortions induced by the readout electronics), and additional operations that are needed due to the complexity and large volume of flight data. CAL operates on long (~30 min) and short (~1 min) sampled data, as well as full-frame images, and produces calibrated pixel flux time series, uncertainties, and other metrics that are used in subsequent Pipeline modules. The raw and calibrated data are also archived in the Multi-mission Archive at Space Telescope at the Space Telescope Science Institute for use by the astronomical community.

Calibration↗
NASA NTRSDate not supplied

Open-Source Data Engineering at NASA: CCMC's Approach to Managing Petabyte-Scale Heliophysics Data

The Community Coordinated Modeling Center (CCMC) at NASA Goddard Space Flight Center (GSFC) leads heliophysics research by providing open access to numerous models and their outputs. Our resources are available on-demand and continuously updated with real-time data, covering sun-earth interactions across multiple domains. These domains include coronal, heliosphere, inner and global magnetosphere, ionosphere, thermosphere, and lower atmosphere interactions. Operating in a hybrid environment, CCMC utilizes both self-owned hardware and Amazon Web Services (AWS) cloud infrastructure. Managing petabytes of data across multiple locations necessitates robust data engineering solutions. To address this challenge, CCMC has adopted industry-standard and open-source tools. We use Apache Airflow as our primary data engineering platform, Python for scripting and data processing, and GitLab for version control and CI/CD. Additionally, we employ Kubernetes for containerized services, Grafana and Prometheus for metrics and monitoring, and Terraform and Puppet for reproducible infrastructure as code. This presentation will discuss lessons learned from our data engineering experiences, platforms evaluated but found unsuitable for our scientific data requirements, and specific techniques developed to enhance data transfer speed and reliability. By using these technologies effectively, CCMC continues to advance heliophysics research through efficient data management and open-access modeling.

space weather↗
NASA NTRSDate not supplied

CFD Validation Study of a Hypersonic Cone-Slice-Flap Variable Geometry Configuration

Model validation is the process of determining the degree of accuracy between physical reality and the model. The result of model validation can either be used to improve the model through calibration or quantify the model-form uncertainty. This work focuses on providing the model-form uncertainty through an area metric for a hypersonic cone-slice-flap variable geometry configuration given uncertainty in both the simulation and experimental data. For a variable geometry, performing uncertainty quantification to capture the model-form uncertainty on every configuration is computationally challenging. This work lays out a procedure that can give an accurate representation of the model-form uncertainty using a small number of high-fidelity runs and many low-fidelity runs on multiple configurations. Running this comparison provides a quantifiable measurement for the accuracy of each turbulence model for this type of design. The high-fidelity CFD solver used was VULCAN-CFD and the low-fidelity results came from Cart3D. The experimental data came from the 20-Inch Mach 6 Tunnel located at NASA Langley Research Center. The present work showed that the turbulence simulation overpredicted the drag and lift coefficient, while underpredicting the pitching moment coefficient. The model-form uncertainty estimate resulted up to a 13.6% change in the total uncertainty for the drag coefficient, up to a 57.4% change in total uncertainty for the lift coefficient, and up to a 100% change in total uncertainty for the pitching moment coefficient.

Laura White↗
NASA NTRS1996

An Analysis of NASA Technology Transfer

A review of previous technology transfer metrics, recommendations, and measurements is presented within the paper. A quantitative and qualitative analysis of NASA's technology transfer efforts is performed. As a relative indicator, NASA's intellectual property performance is benchmarked against a database of over 100 universities. Successful technology transfer (commercial sales, production savings, etc.) cases were tracked backwards through their history to identify the key critical elements that lead to success. Results of this research indicate that although NASA's performance is not measured well by quantitative values (intellectual property stream data), it has a net positive impact on the private sector economy. Policy recommendations are made regarding technology transfer within the context of the documented technology transfer policies since the framing of the Constitution. In the second thrust of this study, researchers at NASA Langley Research Center were surveyed to determine their awareness of, attitude toward, and perception about technology transfer. Results indicate that although researchers believe technology transfer to be a mission of the Agency, they should not be held accountable or responsible for its performance. In addition, the researchers are not well educated about the mechanisms to perform, or policies regarding, technology transfer.

Bush, Lance B.↗
NASA NTRS2011

Using Reliability to Meet Z540.3's 2 percent Rule

NASA's Kennedy Space Center (KSC) undertook implementation of ANSI/NCSL Z540.3-2006 in October 2008. Early in the implementation, KSC identified that the largest cost driver of Z540.3 implementation is measurement uncertainty analyses for legacy calibration processes. NASA, like other organizations, has a significant inventory of measuring and test equipment (MTE) that have documented calibration procedures without documented measurement uncertainties. This paper provides background information to support the rationale for using high in-tolerance reliability as evidence of compliance to the 2% probability of false acceptance (PFA) quality metric of ANSI/NCSL Z540.3-2006 allowing use of qualifying legacy processes. NASA is adopting this as policy and is recommending NCSL International consider this as a method of compliance to Z540.3. Topics covered include compliance issues, using end-of-period reliability (EOPR) to estimate test point uncertainty, reliability data influences within the PFA model, the validity of EOPR data, and an appendix covering "observed" versus "true" EOPR.

Mimbs, Scott M.↗
NASA NTRS2016

Airport Traffic Conflict Detection and Resolution Algorithm Evaluation

Two conflict detection and resolution (CD&R) algorithms for the terminal maneuvering area (TMA) were evaluated in a fast-time batch simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. One CD&R algorithm, developed at NASA, was designed to enhance surface situation awareness and provide cockpit alerts of potential conflicts during runway, taxi, and low altitude air-to-air operations. The second algorithm, Enhanced Traffic Situation Awareness on the Airport Surface with Indications and Alerts (SURF IA), was designed to increase flight crew awareness of the runway environment and facilitate an appropriate and timely response to potential conflict situations. The purpose of the study was to evaluate the performance of the aircraft-based CD&R algorithms during various runway, taxiway, and low altitude scenarios, multiple levels of CD&R system equipage, and various levels of horizontal position accuracy. Algorithm performance was assessed through various metrics including the collision rate, nuisance and missed alert rate, and alert toggling rate. The data suggests that, in general, alert toggling, nuisance and missed alerts, and unnecessary maneuvering occurred more frequently as the position accuracy was reduced. Collision avoidance was more effective when all of the aircraft were equipped with CD&R and maneuvered to avoid a collision after an alert was issued. In order to reduce the number of unwanted (nuisance) alerts when taxiing across a runway, a buffer is needed between the hold line and the alerting zone so alerts are not generated when an aircraft is behind the hold line. All of the results support RTCA horizontal position accuracy requirements for performing a CD&R function to reduce the likelihood and severity of runway incursions and collisions.

Jones, Denise R.↗
NASA NTRS2023

Split-Step Simulations to Assess the Effects of Atmospheric Boundary Layer Turbulence on the Dose Variability of N-Waves and Shaped Booms

The effects of atmospheric boundary layer turbulence on the loudness variability of a sonic boom N-wave and shaped boom are examined with split-step simulations. The shaped boom is representative of a design iteration of the NASA X-59 aircraft. Inhomogeneous atmospheric boundary layer turbulence is generated in the computational domain by a Fourier synthesis method. The N-wave and shaped boom are propagated through turbulent fields representing eight different convection levels measured at the NASA Kennedy Space Center and the NASA Armstrong Flight Research Center. Probability density functions of the formation of caustic regions along the propagation direction are computed from the N-wave results, and a parameter to collapse the caustic PDFs that accounts for both fluctuation intensities and length scales is proposed. Statistical results concerning loudness metric variability are presented, and the standard deviations of several metrics are shown to collapse across different convection levels of turbulence for small nondimensional propagation distances. The loudness metric distributions are observed to be well approximated by a normal distribution for a given range of propagation distances, and become increasingly skewed as distance increases. A model function for the dose variability is proposed, and the function parameters are found to be related to the convection level of the turbulence. The model for the dose variability distribution is compared to simulation data that were not used to find the regression parameters of the model. At several nondimensional propagation distances, agreement is observed between the model and the simulation data. These results indicate that the model may be suitable for providing quick estimates of noise dose variability in the primary carpet region across a wide range of atmospheric boundary layer conditions.

Sonic boom↗