Results for “lead optimization” — Page 45

NASA NTRS2021

Evaluation of Sensor Uncertainty Mitigation Methods for Detect-and-Avoid Systems

The impact of sensor noise on the performance of Detect-And-Avoid (DAA) systems can be reduced by implementing various mitigation schemes. This paper evaluates two such methods. One of them is the Sensor Uncertainty Mitigation (SUM) method, implemented in the Detect and Avoid Alerting Logic for Unmanned Systems (DAIDALUS) algorithm, a reference implementation in the DAA minimum operational performance standards. The second method is the Virtual Intruder State Aggregation (VISA), which averages multiple subsequent intruder states extrapolated to the current (most recent) time into a single ``aggregated`` intruder state. The VISA method can be used either individually as a sensor noise mitigation method in its own right, or in combination with DAIDALUS SUM. The performance of these methods is evaluated using three safety and operational suitability metrics and compared with a baseline configuration using static safety buffers. A large number of encounters representative of low-speed unmanned aircraft against non-cooperative manned aircraft, not equipped with a broadcasting transponder or ADS-B out system, are simulated and evaluated. An air-to-air radar model produces representative sensor noise for the DAA system. Results show that increasing the DAIDALUS SUM parameters for horizontal and vertical uncertainty improves the safety metric at the cost of increasing the number of actionable alerts leading to increased workload. A range of SUM parameters is recommended as suitable values for the type of operations considered for this work. VISA was found to be almost as effective as other noise mitigation methods even when it was used alone. Combining VISA with DAIDALUS SUM achieved the best performance among all investigated methods used with DAIDALUS. General trends and optimal SUM configurations were found to be nearly the same for two large and very different encounter data sets.

Detect-and-Avoid Systems↗

NASA NTRSDate not supplied

Merging Analytic Collaborative Frameworks with New Observing Strategies Toward a Digital Twin: Earth – Episodic Pulse Event Impacts on Ocean Carbon Cycle as an Example

Virtual representations of the Earth will allow us to address some of the most critical environmental issues of our time. Here, we show the first steps toward representation of riverine, estuarine, and coastal carbon processes to enable scenario driven “what-if” analyses of the carbon system and human footprint. Excess sediment and nutrient runoff from land-based human activities impact water quality and can pose serious threats to coastal and marine ecosystems. Episodic pulse events, such as extreme precipitation events, can increase the amount of nutrients entering estuaries and coastal regions, potentially leading to large phytoplankton blooms followed by anoxic conditions. Consequences of coastal runoff are predicted to increase with the higher intensity and frequency of extreme events. Beyond the threat to coastal ecosystems, recent findings suggest these episodic pulses might play a significant role for biological production influencing regional and global carbon fluxes and budgets. An improved understanding of these events through optimal, dynamic observing strategies will increase our knowledge of the land-ocean continuum and how regional events and nutrient fluxes affect the carbon cycle and ocean ecosystem. This conceptual framework enables focused science investigations by pairing data analytics and artificial intelligence tools (otherwise termed an Analytic Center Framework, ACF) with targeted measurement acquisition through distributed sensing and intelligent asset tasking (or New Observing Strategies, NOS). This NOS and ACF iterative approach acquires and integrates complementary and coincident satellite, in-situ and model data to build a more complete and in-depth picture of science phenomena. Specifically, Apache Science Data Analytic Platform (SDAP) is extended to incorporate relevant datasets for data access, harmonized analysis, and anomaly detection. When conditions are met for a likely pulse event, NASA’s D-SHIELD (Distributed Spacecraft with Heuristic Intelligence to Enable Logistical Decisions) tool is triggered to optimize asset overpass frequency and schedule observations for persistent monitoring. Targeted data is ingested by SDAP for enhanced investigation via iterative analysis until the trigger criteria is no longer met - steps toward a digital twin.

Laura Rogers↗

NASA NTRSDate not supplied

Evaluation of Regional Water and Energy Balance in Contemporary Reanalyses

Regional to continental water and energy balance in reanalyses provide crucial information on the climate and climate variations in that region and can contrast other regions. Reanalyses are a valuable tool in piecing together the complete balance owing to the incorporation of the budgets in the background model and the assimilation of observation. On the other hand, the background model has its own biases and observational assimilation can lead to non-negligible tendencies within the budgets, and these can vary over space and time. Here, we will compare the balance within several reanalyses and how they have evolved over recent decades. Several observational data products will provide reference points in the comparison. In addition, a recent project has integrated observations of the water and energy budgets in an optimization that aims to reduce the imbalance of regional budgets in using observational terms from disparate sources. In evaluating the regional balances, we will incorporate, when available, the water and energy convergence terms as well as their analysis increments (which may be diagnosed as residuals). The reanalyses considered here include: Japanese Reanalyses for Three Quarters Century (JRA3Q), ECMWF Reanalysis version 5 (ERA5), Modern Era Retrospective-analysis for Research and Applications version 2 (MERRA-2) and the NCEP Reanalysis II (NCEPR2). NCEPR2 is representative of the late 90s technology, while the others represent the contemporary climate reanalyses presently available. We will discuss the regional balances over key river basins (e.g. Mississippi and Amazon), and a range of continents including those well observed (North America and Europe) and those with fewer consistent observations (e.g. Africa). These contrasting regions show the degree of advancement in reanalyses and expose areas in need of improvement. The results also demonstrate the usefulness of producing complete atmospheric water and energy budgets as part of the diagnostic output.

Michael G Bosilovich↗

NASA NTRSDate not supplied

Evaluation of Regional Water and Energy Balance in Contemporary Reanalyses

Regional to continental water and energy balance in reanalyses provide crucial information on the climate and climate variations in that region and can contrast other regions. Reanalyses are a valuable tool in piecing together the complete balance owing to the incorporation of the budgets in the background model and the assimilation of observation. On the other hand, the background model has its own biases and observational assimilation can lead to non-negligible tendencies within the budgets, and these can vary over space and time. Here, we will compare the balance within several reanalyses and how they have evolved over recent decades. Several observational data products will provide reference points in the comparison. In addition, a recent project has integrated observations of the water and energy budgets in an optimization that aims to reduce the imbalance of regional budgets in using observational terms from disparate sources. In evaluating the regional balances, we will incorporate, when available, the water and energy convergence terms as well as their analysis increments (which may be diagnosed as residuals). The reanalyses considered here include: Japanese Reanalyses for Three Quarters Century (JRA3Q), ECMWF Reanalysis version 5 (ERA5), Modern Era Retrospective-analysis for Research and Applications version 2 (MERRA-2) and the NCEP Reanalysis II (NCEPR2). NCEPR2 is representative of the late 90s technology, while the others represent the contemporary climate reanalyses presently available. We will discuss the regional balances over key river basins (e.g. Mississippi and Amazon), and a range of continents including those well observed (North America and Europe) and those with fewer consistent observations (e.g. Africa). These contrasting regions show the degree of advancement in reanalyses and expose areas in need of improvement. The results also demonstrate the usefulness of producing complete atmospheric water and energy budgets as part of the diagnostic output.

Michael Bosilovich↗

NASA NTRS2008

Distributed Aviation Concepts and Technologies

Aviation has experienced one hundred years of evolution, resulting in the current air transportation system dominated by commercial airliners in a hub and spoke infrastructure. While the first fifty years involved disruptive technologies that required frequent vehicle adaptation, the second fifty years produced a stable evolutionary optimization of decreasing costs with increasing safety. This optimization has resulted in traits favoring a centralized service model with high vehicle productivity and cost efficiency. However, it may also have resulted in a system that is not sufficiently robust to withstand significant system disturbances. Aviation is currently facing rapid change from issues such as environmental damage, terrorism threat, congestion and capacity limitations, and cost of energy. Currently, these issues are leading to a loss of service for weaker spoke markets. These catalysts and a lack of robustness could result in a loss of service for much larger portions of the aviation market. The impact of other competing transportation services may be equally important as casual factors of change. Highway system forecasts indicate a dramatic slow down as congestion reaches a point of non-linearly increasing delay. In the next twenty-five years, there is the potential for aviation to transform itself into a more robust, scalable, adaptive, secure, safe, affordable, convenient, efficient and environmentally friendly system. To achieve these characteristics, the new system will likely be based on a distributed model that enables more direct services. Short range travel is already demonstrating itself to be inefficient with a centralized model, providing opportunities for emergent distributed services through air-taxi models. Technologies from the on-demand revolution in computers and communications are now available as major drivers for aviation on-demand adaptation. Other technologies such as electric propulsion are currently transforming the automobile industry, and will also significantly alter the functionality of future distributed aviation concepts. Many hurdles exist, including technology, regulation, and perception. Aviation has an inherent governmental role not present in other recent on-demand transformations, which may pose a risk of curtailing aviation democratization .

Moore, Mark D.↗

NASA NTRS2019

Effect of Out-Gassing on the Onset of Hypersonic Boundary Layer Transition

Prediction and control of the onset of transition and the associated variation in aerothermodynamic parameters in high-speed flows is key to optimize the performance and design of Thermal Protection Systems (TPS) of next-generation aerospace vehicles [1]. Boundary Layer Transition (BLT) characteristics can influence the surface heating budget determining the TPS thickness and consequently its weight penalty. Ablative heatshields are designed to alleviate the high heat flux at the surface through pyrolysis of their polymeric matrix and subsequent fiber ablation [2]. Pyrolysis leads to out-gassing and non-uniform ablation lead to surface roughness, both of which are known to influence the transition process. An ablator impacts BLT through three main routes: gas injecting into the boundary layer from the wall, changing the surface heat transfer due to wall-flow chemical reactions, and modifying surface roughness [3]. In preparation to Mars 2020 mission post-flight analysis, the predictive transition capability has been initiated toward hard-coupling porous material response analysis and aerothermal environment calculation.

Karimi, Mona↗

NASA NTRSDate not supplied

Natural Language Processing Analysis of Notices to Airmen for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized.

Natural Language Processing↗

NASA NTRSDate not supplied

Natural Language Processing (NLP) Analysis of NOTAMs for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized. Video is an mp4 download, with a play time of 9 min 35 secs.

Natural Language Processing↗

NASA NTRSDate not supplied

Uncovering Hazards Using a Multi-Objective Optimization to Explore the Faulty State-Space

Considering resilience when designing complex engineered systems is crucial to ensure the system is safe under unexpected hazardous scenarios. Traditional risk-based approaches, such as Failure Modes and Effects Analysis (FMEA) are useful for designing the system to mitigate hazardous scenarios that can be identified by the designer, but often require experience or prior knowledge of system failures to generate. More recently, researchers have developed simulation tools that enable the designer to model large sets of hazardous scenarios (driven by both internal faults and external factors) through simulation. While these tools enable a wider scope of fault modes to be evaluated (e.g., by injecting combined set of fault modes or injecting modes at different times), the resulting assessments (like FMEA) still require knowledge of the specific modes to be evaluated. However, failure to analyze a wide variety of fault scenarios can lead to an incomplete picture of the system resilience, especially to "surprise events'' which may be difficult for the designer to identify and predict beforehand. To overcome this challenge, previous work developed a fault sampling approach for resilience simulations which would procedurally-generate a wide variety of potential faults by systematically perturbing the health states of the system. While the resulting fault modes generated covered a much larger space hazards than would be otherwise considered (and identified many unique failure trajectories which would not have otherwise been identified), it also significantly increased the computational cost of the analysis and resulted in the simulation and analysis of a large set of essentially duplicate scenarios. Additionally, as the number of dimensions in the faulty state-space increases, the full elaboration of possible modes becomes computationally infeasible, justifying the use of a more targeted search. To resolve this limitation, this work proposes the use of a multiobjective optimization algorithm to search the health state space for potential fault modes that are both (1) hazardous and (2) unique. To solve this type of problem, this work proposes the use of a cooperative co-evolutionary algorithm. To demonstrate this approach, it will be applied to a model of an autonomous rover which uses line markings to navigate, focusing on potential hazards in the drive system which could cause the rover to crash. To determine the merit of the approach, it will further be compared with the previously-presented range elaboration approach and a random mode generation approach on the basis of computational efficiency and found modes.

Resilience↗

NASA NTRS1977

Influence of temperature change on optimum laminate design

Results of a laminate optimization study, which includes prescribed temperature change and mechanical loading conditions, are presented. Minimum-weight designs for balanced symmetric laminates are obtained subject to strength, membrane stiffness, and minimum thickness requirements, while including and omitting temperature change effects. Based on a first ply failure design philosophy and employing a linear thermoelastic analysis, it is shown that taking temperature decrease effects into account leads to substantial weight penalties in strength critical fiber composite laminates. Numerical results are presented for representative fiber composite materials based on three commonly used combined stress failure criteria.

Schmit, L. A., Jr.↗

NASA NTRS1982

Continuous Czochralski growth. Development of advanced Czochralski growth process to produce low cost 150 kg silicon ingots from a single crucible for technology readiness

The improvement of growth rates using radiation shielding and investigation of the crucible melt interaction for improved yields were emphasized. Growth runs were performed from both 15 and 16 inch diameter crucibles, producing 30 and 37 kg ingots respectively. Efforts to increase the growth rate of 150 mm diameter ingots were limited by temperature instabilities believed to be caused by undesirable thermal convections in the larger melts. The radiation shield improved the growth rate somewhat, but the thermal instability was still evident, leading to nonround ingots and loss of dislocation-free structure. A 38 kg crystal was grown to demonstrate the feasibility of producing 150 kg with four growth cycles. After the grower construction phase, the Hamco microprocessor control system was interfaced to the growth facility, including the sensor for automatic control of seeding temperature, and the sensor for automatic shouldering. Efforts focused upon optimization of the seeding, necking, and shoulder growth automation programs.

Source record↗

NASA NTRS1991

Theoretical study of the bonding of Sc, Y, and La singly charged and dipositive ions to C2H2, C2H4, and C3H6

The interaction of the Sc and Y singly-charged and dipositive ions with C2H2, C2H4, and C3H6 is studied using electronic structure calculations that include high levels of electron correlation. These results are compared with comparable calculations performed previously for La(+) and La(2+). For C2H2 and C2H4, all three metal ions insert into the C-C pi bond, making a three-membered ring. The optimal structures for the MC3H6(+) ions all involve rearrangement to make a four-membered ring. The strength of the metal-ligand bond for the singly charged ions follows the order La greater than Sc equal to about Y. In contrast, the bonds involving the dipositive ions are electrostatic, so that the binding energy increases as the size of the ion decreases, leading to the trend Sc greater than Y greater than La.

Bauschlicher, Charles W., Jr.↗

NASA NTRS1992

An international aerospace information system: A cooperative opportunity

Scientific and technical information (STI) is a valuable resource which represents the results of large investments in research and development (R&D), and the expertise of a nation. NASA and its predecessor organizations have developed and managed the preeminent aerospace information system. We see information and information systems changing and becoming more international in scope. In Europe, consistent with joint R&D programs and a view toward a united Europe, we have seen the emergence of a European Aerospace Database concept. In addition, the development of aeronautics and astronautics in individual nations have also lead to initiatives for national aerospace databases. Considering recent technological developments in information science and technology, as well as the reality of scarce resources in all nations, it is time to reconsider the mutually beneficial possibilities offered by cooperation and international resource sharing. The new possibilities offered through cooperation among the various aerospace database efforts toward an international aerospace database initiative which can optimize the cost/benefit equation for all participants are considered.

Cotter, Gladys A.↗

NASA NTRS2011

Balancing Training Techniques for Flight Controller Certification

Training of ground control teams has been a difficult task in space operations. There are several intangible skills that must be learned to become the steely eyed men and women of mission control who respond to spacecraft failures that can lead to loss of vehicle or crew if handled improperly. And as difficult as training is, it can also be costly. Every day, month or year an operator is in training, is a day that not only they are being trained without direct benefit to the organization, but potentially an instructor or mentor is also being paid for hours spent assisting them. Therefore, optimization of the training flow is highly desired. Recently the Expedition Division (DI) at Johnson Space Flight Center has recreated their training flows for the purpose of both moving to an operator/specialist/instructor hierarchy and to address past inefficiencies in the training flow. This paper will discuss the types of training DI is utilizing in their new flows, and the balance that has been struck between the ideal learning environments and realistic constraints. Specifically, the past training flow for the ISS Attitude Determination and Control Officer will be presented, including drawbacks that were encountered. Then the new training flow will be discussed and how a new approach utilizes more training methods and teaching techniques. We will look at how DI has integrated classes, workshops, checkouts, module reviews, scenarios, OJT, paper sims, Mini Sims, and finally Integrated Sims to balance the cost and timing of training a new flight controller.

Gosling, Christina↗

NASA NTRS1976

Research and development for improved lead-salt diode lasers

A substantial increase in output power levels for lead-salt diode lasers, through the development of improved fabrication methods, as demonstrated. The goal of 1 mW of CW, single-mode, single-ended power output, was achieved, with exceptional devices exhibiting values greater than 8 mW. It was found that the current tuning rate could be controlled by adjusting the p-n junction depth, allowing the tuning rate to be optimized for particular applications. An unexpected phenomenon was encountered when crystal composition was observed to be significantly altered by annealing at temperatures as low as 600 C; the composition was changed by transport of material through the vapor phase. This effect caused problems in obtaining diode lasers with the desired operating characteristics. It was discovered that the present packaging method introduces gross damaging effects in the laser crystal through pressure applied by the C-bend.

Butler, J. F.↗

NASA NTRS1983

A study of helicopter gust response alleviation by automatic control

Two control schemes designed to alleviate gust-induced vibration are analytically investigated for a helicopter with four articulated blades. One is an individual blade pitch control scheme. The other is an adaptive blade pitch control algorithm based on linear optimal control theory. In both controllers, control inputs to alleviate gust response are superimposed on the conventional control inputs required to maintain the trim condition. A sinusoidal vertical gust model and a step gust model are used. The individual blade pitch control, in this research, is composed of sensors and a pitch control actuator for each blade. Each sensor can detect flapwise (or lead-lag or torsionwise) deflection of the respective blade. The acturator controls the blade pitch angle for gust alleviation. Theoretical calculations to predict the performance of this feedback system have been conducted by means of the harmonic method. The adaptive blade pitch control system is composed of a set of measurements (oscillatory hub forces and moments), an identification system using a Kalman filter, and a control system based on the minimization of the quadratic performance function.

Saito, S.↗

NASA NTRS1995

ACTS for distance education in developing countries

The need for electrical energy supply in the rural communities of developing countries has been well documented. Equally well known is the potential for photovoltaic in cost effectively meeting this need. A major impediment to fulfilling the need is the lack of indigenous personnel with a knowledgeof photovoltaic systems, and the associated infrastructure required to implement project. Various delivery schemes for providing the needed training to developing countries personnel have been investigated. Various train methods and programs that have been employed to remedy the problem have had significant drawbacks in terms of cost, consistency, impact, reach, and sustainability. The hypothesis to be tested in this project posits that satellite-based distance education using ACTS technologies can overcome these impediments. The purpose of the project is to investigate the applicability of the ACTS satellite in providing distance education in photovoltaic systems to developing countries and rural communities. An evaluation of the cost effectiveness of using ACTS unique technologies to overcome identified problems shall be done. The limitations of ACTS in surmounting distance education problems in developing countries shall be investigated. This project will, furthermore, provide training to Savannah State College faculty in photovoltaic (PV) systems and in distance education configurations and models. It will also produce training materials adequate for use in PV training programs via distance education. Savannah State College will, as a consequence become well equipped to play a leading role in the training of minority populations in photovoltaic systems and other renewables through its Center for Advanced Water Technology and Energy Systems. This communication provides the project outline including the specific issues that will be investigated during the project. Also presented i the project design which covers the participations of the various components of a network of institutions that is formed for optimal project execution. The expected results and project output, including plans for potential leverages and linkages to be derived, are also discussed. Finally, we point out possible extensions from this project and other related projects that could be initiated based on the experiences gained from the project.

Kalu, A↗

NASA NTRS2002

The Design of Collectives of Agents to Control Non-Markovian Systems

The 'Collective Intelligence' (COIN) framework concerns the design of collectives of reinforcement-learning agents such that their interaction causes a provided 'world' utility function concerning the entire collective to be maximized. Previously, we applied that framework to scenarios involving Markovian dynamics where no re-evolution of the system from counter-factual initial conditions (an often expensive calculation) is permitted. This approach sets the individual utility function of each agent to be both aligned with the world utility, and at the same time, easy for the associated agents to optimize. Here we extend that approach to systems involving non-Markovian dynamics. In computer simulations, we compare our techniques with each other and with conventional-'team games'. We show whereas in team games performance often degrades badly with time, it steadily improves when our techniques are used. We also investigate situations where the system's dimensionality is effectively reduced. We show that this leads to difficulties in the agents' ability to learn. The implication is that 'learning' is a property only of high-enough dimensional systems.

Lawson, John W.↗