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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 NTRS2016

Spitzer Observations of OGLE-2015-BLG-1212 Reveal a New Path toward Breaking Strong Microlens Degeneracies

Spitzer microlensing parallax observations of OGLE-2015-BLG-1212 decisively break a degeneracy between planetary and binary solutions that is somewhat ambiguous when only ground-based data are considered. Only eight viable models survive out of an initial set of 32 local minima in the parameter space. These models clearly indicate that the lens is a stellar binary system possibly located within the bulge of our Galaxy, ruling out the planetary alternative. We argue that several types of discrete degeneracies can be broken via such space-based parallax observations.

Spitzer microlensing parallax observations↗

NASA NTRS1992

Simulator for concurrent processing data flow architectures

A software simulator capability of simulating execution of an algorithm graph on a given system under the Algorithm to Architecture Mapping Model (ATAMM) rules is presented. ATAMM is capable of modeling the execution of large-grained algorithms on distributed data flow architectures. Investigating the behavior and determining the performance of an ATAMM based system requires the aid of software tools. The ATAMM Simulator presented is capable of determining the performance of a system without having to build a hardware prototype. Case studies are performed on four algorithms to demonstrate the capabilities of the ATAMM Simulator. Simulated results are shown to be comparable to the experimental results of the Advanced Development Model System.

Malekpour, Mahyar R.↗

NASA NTRS1989

Knowledge acquisition from natural language for expert systems based on classification problem-solving methods

It is shown how certain kinds of domain independent expert systems based on classification problem-solving methods can be constructed directly from natural language descriptions by a human expert. The expert knowledge is not translated into production rules. Rather, it is mapped into conceptual structures which are integrated into long-term memory (LTM). The resulting system is one in which problem-solving, retrieval and memory organization are integrated processes. In other words, the same algorithm and knowledge representation structures are shared by these processes. As a result of this, the system can answer questions, solve problems or reorganize LTM.

Gomez, Fernando↗

DOE OSTI2020

Photoinduced charge transfer in Zn(II) and Au(III)-ligated symmetric and asymmetric bacteriochlorin dyads: A computational study

The excited-state properties and photoinduced charge-transfer (CT) kinetics in a series of symmetrical and asymmetrical Zn- and Au-ligated meso–meso-connected bacteriochlorin (BChl) complexes are studied computationally. BChl derivatives, which are excellent near-IR absorbing chromophores, are found to play a central role in bacterial photosynthetic reaction centers but are rarely used in artificial solar energy harvesting systems. The optical properties of chemically linked BChl complexes can be tuned by varying the linking group and involving different ligated metal ions. We investigate charge transfer in BChl dyads that are either directly linked or through a phenylene ring (1,4- phenylene) and which are ligating Zn or Au ions. The directly linked dyads with a nearly perpendicular arrangement of the BChl units bear markedly different properties than phenylene linked dyads. In addition, we find that the dielectric dependence of the intramolecular CT rate is very strong in neutral Zn-ligated dyads, whereas cationic Au-ligated dyads show negligible dielectric dependence of the CT rate. Rate constants of the photo induced CT process are calculated at the semiclassical Marcus level and are compared to fully quantum mechanical Fermi’s golden rule based values. The rates are calculated using a screened range separated hybrid functional that offers a consistent framework for addressing environment polarization. We study solvated systems in two solvents of a low and a high scalar dielectric constant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2011

Flight Deck-Based Delegated Separation: Evaluation of an On-Board Interval Management System with Synthetic and Enhanced Vision Technology

An emerging Next Generation Air Transportation System concept - Equivalent Visual Operations (EVO) - can be achieved using an electronic means to provide sufficient visibility of the external world and other required flight references on flight deck displays that enable the safety, operational tempos, and visual flight rules (VFR)-like procedures for all weather conditions. Synthetic and enhanced flight vision system technologies are critical enabling technologies to EVO. Current research evaluated concepts for flight deck-based interval management (FIM) operations, integrated with Synthetic Vision and Enhanced Vision flight-deck displays and technologies. One concept involves delegated flight deck-based separation, in which the flight crews were paired with another aircraft and responsible for spacing and maintaining separation from the paired aircraft, termed, "equivalent visual separation." The operation required the flight crews to acquire and maintain an "equivalent visual contact" as well as to conduct manual landings in low-visibility conditions. The paper describes results that evaluated the concept of EVO delegated separation, including an off-nominal scenario in which the lead aircraft was not able to conform to the assigned spacing resulting in a loss of separation.

Prinzel, Lawrence J., III↗

NASA NTRS1991

Translating expert system rules into Ada code with validation and verification

The purpose of this ongoing research and development program is to develop software tools which enable the rapid development, upgrading, and maintenance of embedded real-time artificial intelligence systems. The goals of this phase of the research were to investigate the feasibility of developing software tools which automatically translate expert system rules into Ada code and develop methods for performing validation and verification testing of the resultant expert system. A prototype system was demonstrated which automatically translated rules from an Air Force expert system was demonstrated which detected errors in the execution of the resultant system. The method and prototype tools for converting AI representations into Ada code by converting the rules into Ada code modules and then linking them with an Activation Framework based run-time environment to form an executable load module are discussed. This method is based upon the use of Evidence Flow Graphs which are a data flow representation for intelligent systems. The development of prototype test generation and evaluation software which was used to test the resultant code is discussed. This testing was performed automatically using Monte-Carlo techniques based upon a constraint based description of the required performance for the system.

Becker, Lee↗

DOE OSTI2025

Advances in supervisory control strategies for a heat pump centric HVAC system − a comprehensive review on applications

There is an increase in research investigating the development and deployment of supervisory controllers that enable high efficiency electrically driven vapor compression heat pumps operating within grid interactive efficient buildings to provide demand side management. This paper reviews over sixty relevant case studies within this domain that focus on commercial off-the-shelf heat pumps whose primary task is providing space conditioning. The concept of a heat pump-centric heating, ventilation, and air-conditioning system is introduced, accompanied by a detailed overview of various kinds of electric heat pumps and building-level thermal energy storage configurations. Additionally, the different types of supervisory controller designs, including rule-based control and model predictive control, are discussed, along with the various methods for communication between a supervisory controller and a downstream heat pump’s local controller. A comparative analysis is conducted in order to categorize the reviewed case studies based on their system design, supervisory control algorithm, and validation methodology. This detailed analysis allows the review to establish current research trends, identify potential gaps, and suggest future directions for the development of this technology. Overall, the authors recommend that more future research be devoted to low-cost practical retrofits that allow for easy integration of active thermal energy storage within heat pump-centric heating, ventilation, and air-conditioning system systems that utilize direct expansion heat pumps. We also suggest more research into the development and deployment of supervisory controllers that can properly communicate with commercial off-the-shelf heat pump local controller available control inputs, e.g., zone temperature setpoint. Lastly, more rigorous experimental demonstrations of advanced supervisory control within real and or closed-loop, transient/ quasi-steady state environments are necessary to reduce industry wide skepticism of this technology.

Demand side management↗

NASA NTRS2003

Pilot Interactions in an Over-Constrained Conflict Scenario as Studied in a Piloted Simulation of Autonomous Aircraft Operations

Feasibility and safety of autonomous aircraft operations were studied in a multi-piloted simulation of overconstrained traffic conflicts to determine the need for, and utility of, priority flight rules to maintain safety in this extraordinary and potentially hazardous situation. An overconstrained traffic conflict is one in which the separation assurance objective is incompatible with other objectives. In addition, a proposed scheme for implementing priority flight rules by staggering the alerting time between the two aircraft in conflict was tested for effectiveness. The feasibility study was conducted through a simulation in the Air Traffic Operations Laboratory at the NASA Langley Research Center. This research activity is a continuation of the Distributed Air-Ground Traffic Management feasibility analysis reported in the 4th USA/Europe Air Traffic Management R&D Seminar in December 2001 (paper #48). The over-constrained conflict scenario studied here consisted of two piloted aircraft that were assigned an identical en-route waypoint arrival time and altitude crossing restriction. The simulation results indicated that the pilots safely resolved the conflict without the need for a priority flight rule system. Occurrences of unnecessary maneuvering near the common waypoint were traced to false conflict alerts, generated as the result of including waypoint constraint information in the broadcast data link message issued from each aircraft. This result suggests that, in the conservative interests of safety, broadcast intent information should be based on the commanded trajectory and not on the Flight Management System flight plan, to which the aircraft may not actually adhere. The use of priority flight rules had no effect on the percentage of the aircraft population meeting completely predictable which aircraft in a given pair would meet the constraints and which aircraft would make the first maneuver to yield right-of-way. Therefore, the proposed scheme for implementing priority flight rules through staggering the alerting time between the two aircraft was completely effective. The data and observations from this experiment, together with results from the previously reported study, support the feasibility of autonomous aircraft operations.

Wing, David J.↗

DOE OSTI2025

Deep reinforcement learning control for co-optimizing energy consumption, thermal comfort, and indoor air quality in an office building

With the recent demand for decarbonization and energy efficiency, advanced HVAC control using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible structures, DRL has been successful in energy reduction for many HVAC systems. However, only a few researches applied DRL agents to manage the entire central HVAC system and control multiple components in both the water loop and the air loop, owing to its complex system structures. Moreover, those researches have not extended their applications by incorporating the indoor air quality, especially both CO2 and PM2.5concentrations, on top of energy saving and thermal comfort, as achieving those objectives simultaneously can cause multiple control conflicts. What's more, DRL agents are usually trained on the simulation environment before deployment, so another challenge is to develop an accurate but relatively simple simulator. Therefore, we propose a DRL algorithm for a central HVAC system to co-optimize energy consumption, thermal comfort, indoor CO2 level, and indoor PM2.5 level in an office building. To train the controller, we also developed a hybrid simulator that decoupled the complex system into multiple simulation models, which are calibrated separately using laboratory test data. The hybrid simulator combined the dynamics of the HVAC system, the building envelope, as well as moisture, CO2, and particulate matter transfer. Three control algorithms (rule-based, MPC, and DRL) are developed, and their performances are evaluated on the hybrid simulator environment with a realistic scenario (i.e., with stochastic noises). The test results showed that, the DRL controller can save 21.4 % of energy compared to a rule-based controller, and has improved thermal comfort, reduced indoor CO2 concentration. The MPC controller showed an 18.6 % energy saving compared to the DRL controller, mainly due to savings from comfort and indoor air quality boundary violations caused by unmeasured disturbances, and it also highlights computational challenges in real-time control due to non-linear optimization. Finally, we provide the practical considerations for designing and implementing the DRL and MPC controllers based on their respective pros and cons.

Guo, Fangzhou↗

DOE OSTI2020

Selectivity-Determining Steps in O 2 Reduction Catalyzed by Iron(tetramesitylporphyrin)

The oxygen reduction reaction (ORR) is the cathode reaction in fuel cells and its selectivity for water over hydrogen peroxide production is important for these technologies. Iron porphyrin catalysts have long been studied for the ORR, but the origins of their selectivity are not well understood because the selectivity-determining step(s) usually occur after the rate-determining step. We report here the effects of acid concentration, as well as other solution conditions such as acid pK a , on the H 2 O 2 /H 2 O selectivity in electrocatalytic ORR by iron(tetramesitylporphyrin) (Fe(TMP)) in DMF. The results show that selectivity reflects a kinetic competition in which the dependence on [HX] is one order greater for the production of H 2 O than H 2 O 2 . Based on such experimental results and computational studies, we propose that the selectivity is governed by competition between protonation of the hydroperoxo intermediate, Fe III (TMP)(OOH), to produce water versus dissociation of the HOO – ligand to yield H 2 O 2 . The data rule out a bifurcation based on the regioselectivity of protonation of the hydroperoxide, as suggested in the enzymatic systems. Furthermore, the analysis developed in this paper should be generally valuable to the study of selectivity in other multi-proton/multi-electron electrocatalytic reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1982

Electron lithography STAR design guidelines. Part 2: The design of a STAR for space applications

The STAR design system developed by NASA enables any user with a logic diagram to design a semicustom digital MOS integrated circuit. The system is comprised of a library of standard logic cells and computr programs to place, route, and display designs implemented with cells from the library. Also described is the development of a radiation-hard array designed for the STAR system. The design is based on the CMOS silicon gate technology developed by SANDIA National Laboratories. The design rules used are given as well as the model parameters developed for the basic array element. Library cells of the CMOS metal gate and CMOS silicon gate technologies were simulated using SPICE, and the results are shown and compared.

Trotter, J. D.↗

NASA NTRS2012

LogScope

LogScope is a software package for analyzing log files. The intended use is for offline post-processing of such logs, after the execution of the system under test. LogScope can, however, in principle, also be used to monitor systems online during their execution. Logs are checked against requirements formulated as monitors expressed in a rule-based specification language. This language has similarities to a state machine language, but is more expressive, for example, in its handling of data parameters. The specification language is user friendly, simple, and yet expressive enough for many practical scenarios. The LogScope software was initially developed to specifically assist in testing JPL s Mars Science Laboratory (MSL) flight software, but it is very generic in nature and can be applied to any application that produces some form of logging information (which almost any software does).

Havelund, Klaus↗

NASA NTRS2020

UAS Service Supplier Network Performance

This report summarizes the performance of Unmanned Aircraft System (UAS) Service Suppliers (USS) in the Technical Capability Level 4 (TCL4) flight test performed by NASA and its partners in support of the UAS Traffic Management (UTM) concept. TCL4 is the final in a series of TCL demonstrations of a traffic management system for small UAS (sUAS). All demonstrations have been executed in collaboration with industry partners. The [FAA 2018] UTM Concept of Operations document describes UTM as:...the manner in which the FAA will support operations for predominantly sUAS operating in low altitude airspace. UTM utilizes industry’s ability to supply services under FAA’s regulatory authority where these services do not currently exist. It is a community-based traffic management system, where the Operators are responsible for the coordination, execution, and management of operations, with rules of the road established by FAA. UTM is designed to support the demand and expectations for a broad spectrum of operations with ever-increasing complexity and risk. UTM should be considered a collection of services rather than a monolithic application. The following section describes the architecture at a high level. For further insight, the FAA’s concept document [FAA 2018] or NASA’s earlier concept publication [NASA 2016] should be consulted.

Rios, Joseph L.↗

NASA NTRS2021

A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction

Airport configuration selection is a complex decision-making process that involves several operational and human factors. In this paper we propose a novel recursive multi-step machine learning (ML) approach to predict airport configuration. The multi-step approach guarantees stability of the predicted configuration by taking as input the configuration predicted at the previous time step. The features of the proposed model include weather data, future arrival and departure counts and current configuration. Due to the importance of arrival and departure counts in predicting the airport configuration, arrival counts are calculated using landing time predictions selected from physics-based landing time predictions available in FAA System Wide Information Management data feeds for each flight. The selection rules were developed and refined to select the most accurate time for different phases of flight. The proposed model predicts the airport configurations up to 6 hours ahead. In this paper we show the predictive performance of the proposed model for six major US airports, including Charlotte Douglas International Airport (CLT), Dallas/Fort Worth International Airport (DFW), John F. Kennedy International Airport (JFK), Newark Liberty International Airport (EWR), LaGuardia Airport (LGA) and Dallas Love Field Airport (DAL). We trained and evaluated models on 2019 and 2020 data in order to study the effect of the pandemic and how changes in traffic patterns affected the performance of the proposed model. Results are compared with a baseline assuming no airport configuration changes. In our results for DFW, we obtained a prediction accuracy of 89.3% for 3 hours ahead prediction, and 82.8% for 6 hours ahead when applied on 2019 data.

machine learning↗

NASA NTRS2021

A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction

machine learning↗

NASA NTRS1989

Expert systems for automated maintenance of a Mars oxygen production system

A prototype expert system was developed for maintaining autonomous operation of a Mars oxygen production system. Normal operation conditions and failure modes according to certain desired criteria are tested and identified. Several schemes for failure detection and isolation using forward chaining, backward chaining, knowledge-based and rule-based are devised to perform several housekeeping functions. These functions include self-health checkout, an emergency shut down program, fault detection and conventional control activities. An effort was made to derive the dynamic model of the system using Bond-Graph technique in order to develop the model-based failure detection and isolation scheme by estimation method. Finally, computer simulations and experimental results demonstrated the feasibility of the expert system and a preliminary reliability analysis for the oxygen production system is also provided.

Ash, Robert L.↗

DOE OSTI2022

Auto Procedure Parsing: A Natural Language Processing Approach

Nuclear Power Plant (NPP) operating procedure is “a set of rules that describes how actions on the plant should be made if a certain system goal should be accomplished. U.S. NPPs use paper-based procedures (PBPs). PBPs are difficult to use. Common errors with PBPs are: following the wrong procedure, omit a step etc. Computer based procedures (CPBs) offer great improvement in ensuring plant safety. Some studies rely on experienced operators to understand the procedure content and then reorganize the procedure with digitally executable capabilities. Other studies utilize the procedure format to design rules to extract information from the operating procedures. Existing studies in procedure parsing are manual, laborious and extract limited information. This study aims to automatically extract critical information from operating procedures for generating computer interpretable representation of procedures. Such representation can further be used for automatic dynamic human reliability analysis and CPB design etc.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Site demonstration and performance evaluation of MPC for a large chiller plant with TES for renewable energy integration and grid decarbonization

Thermal energy storage (TES) for a cooling plant is a crucial resource for load flexibility. Traditionally, simple, heuristic control approaches, such as the storage priority control which charges TES during the nighttime and discharges during the daytime, have been widely used in practice, and shown reasonable performance in the past benefiting both the grid and the end-users such as buildings and district energy systems. However, the increasing penetration of renewables changes the situation, exposing the grid to a growing duck curve, which encourages the consumption of more energy in the daytime, and volatile renewable generation which requires dynamic planning. The growing pressure of diminishing greenhouse gas emissions also increases the complexity of cooling TES plant operations as different control strategies may apply to optimize operations for energy cost or carbon emissions. This paper presents a model predictive control (MPC), site demonstration and evaluation results of optimal operation of a chiller plant, TES and behind-meter photovoltaics for a campus-level district cooling system. The MPC was formulated as a mixed-integer linear program for better numerical and control properties. Compared with baseline rule-based controls, the MPC results show reductions of the excess PV power by around 25%, of the greenhouse gas emission by 10%, and of peak electricity demand by 10%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗