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At least 613 records · Page 34

NASA Glenn's Contributions to Aircraft Engine Noise Research

This presentation reviews engine noise research conducted at the NASA Glenn Research Center over the past 70 years. This report includes a historical perspective of the Center and the facilities used to conduct the research. Major noise research programs are highlighted to show their impact on industry and on the development of aircraft noise reduction technology. Noise reduction trends are discussed, and future aircraft concepts are presented. Since the 1960s, research results show that the average perceived noise level has been reduced by about 20 decibels (dB). Studies also show that, depending on the size of the airport, the aircraft fleet mix, and the actual growth in air travel, another 15 to 17 dB reduction will be required to achieve NASAs long-term goal of providing technologies to limit objectionable noise to the boundaries of an average airport.

Engine Noise↗

Enviromnental Control and Life Support Systems for Mars Missions - Issues and Concerns for Planetary Protection

Planetary protection represents an additional set of requirements that generally have not been considered by developers of technologies for Environmental Control and Life Support Systems (ECLSS). Planetary protection guidelines will affect the kind of operations, processes, and functions that can take place during future human planetary exploration missions. Ultimately, there will be an effect on mission costs, including the mission trade space when planetary protection requirements begin to drive vehicle deisgn in a concrete way. Planetary protection requirements need to be considered early in technology development and mission programs in order to estimate these impacts and push back on requirements or find efficient ways to perform necessary functions. It is expected that planetary protection will be a significant factor during technology selection and system architecture design for future missions.

Barta, Daniel J.↗

New York City Panel on Climate Change 2019 Report Chapter 9: Perspectives on a City in a Changing Climate 2008-2018

Cities experience multiple environmental shifts, stresses, and shocks—such as air and water pollution—and a variety of extreme events simultaneously and continuously. Current urban programs have focused on limiting the impacts of these conditions through a portfolio of multifaceted strategies, such as regulations and codes, management and restoration projects, and citizen engagement. Global climate change represents a new environmental dynamic to which cities now have to respond. While global climate change by definition has impacts world wide, residents and managers of cities, like New York, typically perceive changes in their own local environments. In most cities, temperature is warming with increasingly hotter and longer heatwaves, and heavier downpours are leading to more frequent inland flooding. In coastal cities, sea levels are rising, exacerbating coastal flooding. Analyzing and understanding the impacts of climate change on cities is important because of the dramatic growth in urban populations throughout the world. An estimated nearly 4.0 billion people reside in urban areas, accounting for 52% of the world’s population (UN, 2017). That percentage will increase dramatically in the coming decades as almost all of the growth to take place up to 2050 will be in urban areas (UN, 2017). The New York City metropolitan region (NYMR)—the five boroughs (equivalent to counties) of New York City and the adjacent 26 counties in the states of New York, New Jersey, and Connecticut—is an ideal model of an urban agglomeration. Approximately 8.6 million people live in the five boroughs and more than 15 million people live in the neighboring smaller cities, towns, and villages (City of New York, 2018a; US Census, 2017). The population of the five boroughs is projected to add 1 million people by 2030, while the total region is projected to reach 26.1 million (NYTC, 2015).

Solecki, William↗

Bayesian Model Selection for Reducing Bloat and Overfitting in Genetic Programming for Symbolic Regression

When performing symbolic regression using genetic programming, overfitting and bloat can negatively impact generalizability and interpretability of the resulting equations as well as increase computation times. A Bayesian fitness metric is introduced and its impact on bloat and overfitting during population evolution is studied and compared to common alternatives in the literature. The proposed approach was found to be more robust to noise and data sparsity in numerical experiments, guiding evolution to a level of complexity appropriate to the dataset. Further evolution of the population resulted not in overfitting or bloat, but rather in slight simplifications in model form. The ability to identify an equation of complexity appropriate to the scale of noise in the training data was also demonstrated. In general, the Bayesian model selection algorithm was shown to be an effective means of regularization which resulted in less bloat and overfitting when any amount of noise was present in the training data.

G F Bomarito↗

Brayton Cycle Power Conversion Model for MW-Class Nuclear Electric Propulsion Mars Missions

A Brayton cycle based power conversion system for a nuclear electric propulsion application was modeled in Simulink as part of NASA’s space nuclear program in order to explore the impact of technology assumptions on the power conversion system performance and capabilities. The thermodynamic processes and algorithms within the model are documented, including a higher fidelity reactor model. Assumptions are chosen based on literature and subject matter expert review, and example results and capabilities of the model are shown. The effects of the turbine inlet and compressor inlet temperature on radiator area and thermal efficiency are discussed. For a He-Xe closed Brayton cycle, radiator areas as low as 650 m2/MWe are shown, with corresponding thermal efficiences at roughly 20% for the minimal radiator area solutions.

Brayton↗

Bayesian Model Selection for Reducing Bloat and Overfitting in Genetic Programming for Symbolic Regression

When performing symbolic regression using genetic programming, overfitting and bloat can negatively impact generalizability and interpretability of the resulting equations as well as increase computation times. A Bayesian fitness metric is introduced and its impact on bloat and overfitting during population evolution is studied and compared to common alternatives in the literature. The proposed approach was found to be more robust to noise and data sparsity in numerical experiments, guiding evolution to a level of complexity appropriate to the dataset. Further evolution of the population resulted not in overfitting or bloat, but rather in slight simplifications in model form. The ability to identify an equation of complexity appropriate to the scale of noise in the training data was also demonstrated. In general, the Bayesian model selection algorithm was shown to be an effective means of regularization which resulted in less bloat and overfitting when any amount of noise was present in the training data.

Uncertainty quantification↗

TC3 Overview

This presentation gives an overview of the technology, methods and processes developed during the TC3 Technical Challenge of the System-Wide Safety (SWS) project. The presentation goes over the motivation for doing this research, gives an overview of the tool, methods and process developed under this program, and describes case studies and impact in industry.

Software assurance↗

Critical Developments Made Through the Sounding Rocket Program

Scientists have flown scientific instruments on sub-orbital rockets since the years following World War II when excess rocket motors were made available. Much of our knowledge of heliophysics and astrophysics that now seem well accepted and commonplace have been discovered through the sounding rocket program. The program has also been key in both developing technologies and training scientists and engineers, which have allowed for instruments to be developed for long-term operations satellites. In this talk, I will review critical developments that emerged from the sounding rocket program that have had a lasting impact on our fields.

Amy Winebarger↗

Medical Resource Set Bulky Item Trade Space Analysis for Spaceflight Medical Risk

The NASA engineering community utilizes event-driven and fault-tree probabilistic techniques to classify risks in the space environment by taking advantage of the inherent knowledge of complex spaceflight system design and testing to quantify failure risk. In harmonizing the risk of human space flight, answering the question of ‘How do we balance health, performance and resource risks with other engineering risks on long duration space missions?’ remains a deeply challenging and largely qualitative practice. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is one aspect of the efforts by NASA’s Human Research Program (HRP) to quantitatively assess the impact of health and performance risk. One of MEDPRAT’s key features is its high degree of computational efficiency. Coupled with the HRP High Performance Compute cluster located at NASA’s Glenn Research Center, MEDPRAT runs millions of simulated missions in a matter of minutes. This degree of computational efficiency provides the novel opportunity to explore the relationship between medical set mass, volume, and medical resource size. Of particular interest for future human spaceflight missions are ‘bulky’ items, medical resources like devices, which occupy a large portion of the small, allocated mass and volume for the medical set leaving less room for other resources. This talk will present results showing the quantitative impact of forced inclusion of several bulky items across a variety of medical kit constraints, and the effect that a potential research investment into reducing the bulky item mass and volume may have on risk.

Lauren Mcintyre↗

Demonstration of Rapid Development Through Containerization: OSE-SAT

Modern advancements in spacecraft technology have enabled engineers to develop radically smaller and lighter spacecraft, which has drastically reduced the cost of putting spacecraft into space. Despite these advancements and the shrinking cost to get spacecraft into space, space exploration is still prohibitively expensive. So much so that many space missions prefer to err on the side of caution than take on additional risk by trying newer, unproven technologies. This risk-averse mission design, while very reasonable from a program management point of view, significantly impacts engineers’ ability to solve newer, more complicated problems and limits scientists’ ability to develop more complex experiments that rely on newer technology. Often these new technologies remain stuck at lower technology readiness levels for many years due to the space community's reluctance to take on the additional risks of proving out unproven technology. The Distributed Spacecraft Autonomy (DSA) team at NASA Ames Research Center is developing a containerized solution to enable the rapid development of newer space technologies and accelerate their adoption into space missions. The Opportunistic Software Experiments for Spacecraft Autonomy Testbeds (OSE-SAT) is an on-orbit test bed that aims to reduce the amount of risk associated with newer, unproven space technologies by containerizing each experiment in its own isolated environment and providing a safe, robust, and controlled interface to access spacecraft host resources that is monitored in real time by thoroughly tested Trusted Container developed by DSA. This paper will describe DSA’s implementation of OSE-SAT and discuss the benefits, as well as challenges, of on-orbit containerization.

Aaron J Woodard↗

Airport noise impact reduction through operations

The airport-noise levels and annoyance model (ALAMO) developed at NASA Langley Research Center is comprised of a system of computer programs which is capable of quantifying airport community noise impact in terms of noise level, population distribution, and human subjective response to noise. The ALAMO can be used to compare the noise impact of an airport's current operating scenario with the noise impact which would result from some proposed change in airport operations. The relative effectiveness of number of noise-impact reduction alternatives is assessed for a major midwest airport. Significant reductions in noise impact are predicted for certain noise abatement strategies while others are shown to result in relatively little noise relief.

Deloach, R.↗

Impact of Different Trajectory Option Set Participation Levels within an Air Traffic Management Collaborative Trajectory Option Program

This paper presents the methodology and results of a Human-In-The-Loop (HITL) simulation study conducted in the Airspace Operations Laboratory at NASA Ames Research Center. This study is a part of NASA's ongoing research into developing an Integrated Demand Management (IDM) concept, whose aim is to improve traffic flow management (TFM) by coordinating the FAA's strategic Traffic Flow Management System (TFMS) with its more tactical Time-Based Flow Management (TBFM) system. The purpose of TFM is to regulate air traffic demand so that it is delivered efficiently through constrained airspace resources without exceeding their capacity limits. The IDM concept leverages a new TFMS capability called the Collaborative Trajectory Options Program (CTOP) to strategically pre-condition traffic demand flowing into a TBFM-managed arrival environment, where TBFM is responsible for managing traffic tactically by generating precise arrival schedules. Unlike other TFM tools, CTOP gives flight operators the option of submitting a set of user-preferred alternative trajectories for each flight. CTOP can then use these trajectory option sets (or TOSs) to find user-preferred alternative routes to reduce demand on an overloaded resource. CTOP's effectiveness in redistributing demand is limited, however, by the availability of flights with alternative routes. The research presented in this paper focuses on evaluating the impact on TFM operations by varying the percentage of flights that submit a multiple-option TOS ('TOS participation levels'). Results show the impact on overall system performance and on the rerouted flights themselves. The simulation used a Newark (EWR) airport arrival scenario, with en route weather affecting traffic inbound from the west. Participants were asked to control each of the three arrival flows (north, west, and south) to meet their individual capacity constraints while simultaneously ensuring efficient utilization of the capacity at the destination airport. A large, permeable convective weather cell located southeast of Chicago severely reduced the capacity of the west flow. The study evaluated the impact of five different TOS participation levels on CTOP's ability to re-allocate traffic from the west and improve TFM performance in terms of delay assignment and traffic delivery rate to the airport. Overall, the results showed that increasing TOS submissions allowed the overall system delays to be reduced and fairly distributed among the three arrival flows, at the same time achieving the airport throughput rate. Moreover, it was found that aircraft who submitted a TOS saw a greater reduction in delay, even when they were assigned longer routes. This was particularly true when fewer aircraft submitted a TOS. The results confirm that the CTOP operations with higher TOS participation levels helped utilize the overall National Airspace System (NAS) resources as well as benefited the users who participated.

Yoo, Hyo-Sang↗

Predicting Ground Delay Program at an Airport Based on Meteorological Conditions

In this paper, we present two supervised-learning models, logistic regression and decision tree, to predict occurrence of ground delay program at an airport based on meteorological conditions and scheduled traffic demand. Such predictive capabilities can help the Federal Aviation Administration traffic managers and airline dispatchers to prepare mitigation strategies to reduce the impact of adverse weather. The models are applied to predict ground delay program occurrence at two major U.S. airports: Newark Liberty Intl. and San Francisco Intl. airports. The logistic regression model estimates the probability that a ground delay program will occur during a given hour. Decision tree, on the other hand, classifies an hour as a ground delay program or not based on the input variables. Results indicate that both models perform significantly better than a purely random prediction of ground delay program occurrence at the two airports. The logistic regression model performs better than the decision tree model. The degree to which various input variables impact the probability of ground delay program vary between the two airports. While the enroute convective weather is a dominant factor causing ground delay programs at New York airports, poor visibility and low cloud ceiling caused by marine stratus are major drivers of ground delay programs at San Francisco Intl. airport.

traffic flow management↗

The Spaceguard Survey: Report of the NASA International Near-Earth-Object Detection Workshop

Impacts by Earth-approaching asteroids and comets pose a significant hazard to life and property. Although the annual probability of the Earth being struck by a large asteroid or comet is extremely small, the consequences of such a collision are so catastrophic that it is prudent to assess the nature of the threat and to prepare to deal with it. The first step in any program for the prevention or mitigation of impact catastrophes must involve a comprehensive search for Earth-crossing asteroids and comets and a detailed analysis of their orbits. At the request of the U.S. Congress, NASA has carried out a preliminary study to define a program for dramatically increasing the detection rate of Earth-crossing objects, as documented in this workshop report.

Morrison, David↗

Oceanic Observations

For many years, merchant ships and the naval fleets of various countries have been the major source of data over and in the open ocean. Oceanographic research experiments and process studies in the field have also contributed to the climatological data bases for the global ocean, but, for the most part, these have been limited in duration and extent. However, over the last 10 years under the auspices of the World Climate Research Program and the International Geosphere Biosphere Program the role of the oceans in global and climate change has taken on increased significance. This has created a need for a considerably improved understanding of the seasonal, interannual, decadal and longer time-scale variability of the physical and biogeochemical attributes of the global ocean. As a result, over the past 10 years several major international field programs have been implemented and have had a tremendous impact on the number of in situ observations obtained for the global ocean. The Tropical Ocean Global Atmosphere (TOGA) program, the World Ocean Circulation Experiment (WOCE), and the Joint Global Ocean Flux Study (JGOFS) were designed with observational, modelling, and process study components aimed at analyzing different aspects of the ocean's role in the coupled climate system. In parallel with the field programs, continuous space-based observations of sea surface temperature, sea surface topography, and sea surface winds spanning nearly a decade or longer have become a reality. During this same time period, numerical ocean models and computational power have advanced to the point where the oceanographic observations, both in situ and remotely sensed, can be assimilated into numerical ocean models in order to provide a four-dimensional (x-y-z-t) depiction of the evolving state of the global ocean.

Busalacchi, Antonio J.↗

Case Studies in Crewed Spacecraft Environmental Control and Life Support System Process Compatibility and Cabin Environmental Impact

Contamination of a crewed spacecraft's cabin environment leading to environmental control and life support system (ECLSS) functional capability and operational margin degradation or loss can have an adverse effect on NASA's space exploration mission figures of merit-safety, mission success, effectiveness, and affordability. The role of evaluating the ECLSS's compatibility and cabin environmental impact as a key component of pass trace contaminant control is presented and the technical approach is described in the context of implementing NASA's safety and mission success objectives. Assessment examples are presented for a variety of chemicals used in vehicle systems and experiment hardware for the International Space Station program. The ECLSS compatibility and cabin environmental impact assessment approach, which can be applied to any crewed spacecraft development and operational effort, can provide guidance to crewed spacecraft system and payload developers relative to design criteria assigned ECLSS compatibility and cabin environmental impact ratings can be used by payload and system developers as criteria for ensuring adequate physical and operational containment. In additional to serving as an aid for guiding containment design, the assessments can guide flight rule and procedure development toward protecting the ECLSS as well as approaches for contamination event remediation.

Perry, J. L.↗

Developments in impact damage modeling for laminated composite structures

Damage tolerance is the most critical technical issue for composite fuselage structures studied in the Advanced Technology Composite Aircraft Structures (ATCAS) program. The objective here is to understand both the impact damage resistance and residual strength of the laminated composite fuselage structure. An understanding of the different damage mechanisms which occur during an impact event will support the selection of materials and structural configurations used in different fuselage quadrants and guide the development of analysis tools for predicting the residual strength of impacted laminates. Prediction of the damage state along with the knowledge of post-impact response to applied loads will allow for engineered stacking sequencies and structural configurations; intelligent decisions on repair requirements will also result.

Dost, Ernest F.↗

Systems Engineering Using Heritage Spacecraft Technology: Lessons Learned from Discovery and New Frontiers Deep Space Missions

In the design and development of complex spacecraft missions, project teams frequently assume the use of advanced technology or heritage systems to enable a mission or reduce the overall mission risk and cost. As projects proceed through the development life cycle, increasingly detailed knowledge of the advanced or heritage systems and the system environment identifies unanticipated issues that result in cost overruns or schedule impacts. The Discovery & New Frontiers (D&NF) Program Office recently studied cost overruns and schedule delays resulting from advanced technology or heritage assumptions for 6 D&NF missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that the cost and schedule growth did not result from technical hurdles requiring significant technology development. Instead, systems engineering processes did not identify critical issues early enough in the design cycle to ensure project schedules and estimated costs address the inherent risks. In general, the overruns were traceable to: inadequate understanding of the heritage system s behavior within the proposed spacecraft design and mission environment; an insufficient level of experience with the heritage system; or an inadequate scoping of the system-wide impacts necessary to implement the heritage or advanced technology. This presentation summarizes the study s findings and offers suggestions for improving the project s ability to identify and manage the risks inherent in the technology and heritage design solution.

Barley, Bryan↗