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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures

Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.

Thermodynamics↗
DOE OSTI2021

Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces

The performance of functional materials is dictated by chemical and structural properties of individual atomic sites. In catalysts, for instance, the thermodynamic stability of constituting atomic sites is a key descriptor from which more complex properties, such as molecular adsorption energies and reaction rates, can be derived. In this study, we present a widely applicable machine learning (ML) approach to instantaneously compute the stability of individual atomic sites in structurally and electronically complex nano-materials. Conventionally, we determine such site stabilities using computationally intensive first-principles calculations. With our approach, we predict the stability of atomic sites in sub-nanometer metal clusters of 3–55 atoms with mean absolute errors in the range of 0.11–0.14 eV. To extract physical insights from the ML model, we introduce a genetic algorithm (GA) for feature selection. This algorithm distills the key structural and chemical properties governing the stability of atomic sites in size-selected nanoparticles, allowing for physical interpretability of the models and revealing structure–property relationships. The results of the GA are generally model and materials specific. In the limit of large nanoparticles, the GA identifies features consistent with physics-based models for metal–metal interactions. By combining the ML model with the physics-based model, we predict atomic site stabilities in real time for structures ranging from sub-nanometer metal clusters (3–55 atom) to larger nanoparticles (147 to 309 atoms) to extended surfaces using a physically interpretable framework. Finally, we present a proof of principle showcasing how our approach can determine stable and active nanocatalysts across a generic materials space of structure and composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Machine Learning and IAST-Aided High-Throughput Screening of Cationic and Silica Zeolites for Alkane Capture, Storage, and Separations

We present an approach for quantitatively predicting the temperature-dependent single-component adsorption behavior of linear alkanes in silica and Na-exchanged cationic zeolites using machine learning (ML) models trained from extensive molecular simulations based on force fields with coupled cluster accuracy. A high-performing classification model was developed to distinguish between instances with negligible and non-negligible adsorption. Subsequently, two ML models were trained to predict the single-component adsorption loading and the heat of adsorption at any pressure at 300 K for any zeolite topology and silicon-to-aluminum ratio. The ML models were trained on International Zeolite Association (IZA) zeolites, and their transferability to hypothetical zeolites was successfully validated. We then expand the power of these predictions to adsorbed mixtures at arbitrary temperatures by integrating them with the Clausius–Clapeyron equation and ideal adsorbed solution theory (IAST). This approach was validated and then applied to a temperature swing adsorption separation process to demonstrate its practical utility. We demonstrate how predictions from this ML-enabled approach can allow the selection of high-performing materials that are then validated using detailed molecular simulations based on quantitatively accurate force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

SU-F-T-285: Evaluation of a Patient DVH-Based IMRT QA System

Purpose: To evaluate the clinical performance of a patient DVH-based QA system for prostate VMAT QA. Methods: Mobius3D(M3D) is a QA software with an independent beam model and dose engine. The MobiusFX(MFX) add-on predicts patient dose using treatment machine log files. We commissioned the Mobius beam model in two steps. First, the stock beam model was customized using machine commissioning data, then verified against the TPS with 12 simple phantom plans and 7 clinical 3D plans. Secondly, the Dosimetric Leaf Gap(DLG) in the Mobius model was fine-tuned for VMAT treatment based on ion chamber measurements for 6 clinical VMAT plans. Upon successful commissioning, we retrospectively performed IMRT QA for 12 VMAT plans with the Mobius system as well as the ArcCHECK-3DVH system. Selected patient DVH values (PTV D95, D50; Bladder D2cc, Dmean; Rectum D2cc) were compared between TPS, M3D, MFX, and 3DVH. Results: During the first commissioning step, TPS and M3D calculated target Dmean for 3D plans agree within 0.7%±0.7%, with 3D gamma passing rates of 98%±2%. In the second commissioning step, the Mobius DLG was adjusted by 1.2mm from the stock value, reducing the average difference between MFX calculation and ion chamber measurement from 3.2% to 0.1%. In retrospective prostate VMAT QA, 5 of 60 MFX calculated DVH values have a deviation greater than 5% compared to TPS. One large deviation at high dose level was identified as a potential QA failure. This echoes the 3DVH QA result, which identified 2 instances of large DVH deviation on the same structure. For all DVH’s evaluated, M3D and MFX show high level of agreement (0.1%±0.2%), indicating that the observed deviation is likely from beam modelling differences rather than delivery errors. Conclusion: Mobius system provides a viable solution for DVH based VMAT QA, with the capability of separating TPS and delivery errors.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1984

Limiting mechanisms in large-grain polycrystalline silicon Spatial homogeneity

An experiment to investigate the spatial homogeneity of large-grain polycrystalline silicon shows a number of performance-loss mechanisms. Arrays of up to 400 small (about 0.2 sq cm in area) photodiodes were fabricated on a selection of 10 cm x 10 cm polycrystalline silicon wafers. Measurements of the illuminated current-voltage (J-V) characteristics were used to generate maps of Voc, Jsc, and FF as a function of position; and dark J-V and LBIC analysis were used to determine the cause of low performance in areas with significantly degraded J-V characteristics. In addition to the presence of inclusions, which act as resistive shunts, the performance of many of the cells is limited by quasineutral recombination current, which may vary by up to an order of magnitude across a wafer. The increase is the result of either electrically-active grain boundaries or numerous subgrain boundaries within the grain bulk. In other isolated instances, the open-circuit voltage is reduced by excess space-charge recombination current that is not correlated with either grain or subgrain boundary activity.

Culik, J.↗
NASA NTRS2004

Collaborative Aerospace Research and Fellowship Program at NASA Glenn Research Center

During the summer of 2004, a 10-week activity for university faculty entitled the NASA-OAI Collaborative Aerospace Research and Fellowship Program (CFP) was conducted at the NASA Glenn Research Center in collaboration with the Ohio Aerospace Institute (OAI). This is a companion program to the highly successful NASA Faculty Fellowship Program and its predecessor, the NASA-ASEE Summer Faculty Fellowship Program that operated for 38 years at Glenn. The objectives of CFP parallel those of its companion, viz., (1) to further the professional knowledge of qualified engineering and science faculty,(2) to stimulate an exchange of ideas between teaching participants and employees of NASA, (3) to enrich and refresh the research and teaching activities of participants institutions, and (4) to contribute to the research objectives of Glenn. However, CFP, unlike the NASA program, permits faculty to be in residence for more than two summers and does not limit participation to United States citizens. Selected fellows spend 10 weeks at Glenn working on research problems in collaboration with NASA colleagues and participating in related activities of the NASA-ASEE program. This year's program began officially on June 1, 2004 and continued through August 7, 2004. Several fellows had program dates that differed from the official dates because university schedules vary and because some of the summer research projects warranted a time extension beyond the 10 weeks for satisfactory completion of the work. The stipend paid to the fellows was $1200 per week and a relocation allowance of $1000 was paid to those living outside a 50-mile radius of the Center. In post-program surveys from this and previous years, the faculty cited numerous instances where participation in the program has led to new courses, new research projects, new laboratory experiments, and grants from NASA to continue the work initiated during the summer. Many of the fellows mentioned amplifying material, both in undergraduate and graduate courses, on the basis of the summer s experience at Glenn. A number of 2004 fellows indicated that proposals to NASA will grow out of their summer research projects. In addition, some journal articles and NASA publications will result from this past summer s activities. Fellows from past summers continue to send reprints of articles that resulted from work initiated at Glenn. This report is intended primarily to summarize the research activities comprising the 2004 CFP Program at Glenn. Particular research studies include: 1) Development of an Imaging-Based, Computational Fluid Dynamics Tool to Assess Fluid Mechanics in Experimental Models that Simulate Blood Vessels; 2) Analysis of Nanomaterials Produced from Precursors; and 3) LEO Propagation Analysis Tool.

Heyward, Ann O.↗
DOE OSTI2019

AN APPROACH TO BRINGING AUTOMATED FAULT DETECTION AND DIAGNOSIS (AFDD) TOOLS FOR HVAC&R INTO THE MAINSTREAM

Heating, ventilation and air-conditioning (HVAC) systems can consume over 5 quads of energy annually, representing 30% of energy consumption in the U.S. in commercial buildings. Additionally, commercial refrigeration (R) systems add about 2 quads to commercial buildings energy consumption. Most HVAC systems have one or more faults (low/high refrigerant charge, valve leakage, condenser/evaporator fouling, filter/dryer restriction, economizer faults, controls faults) that result in increased energy consumption. Automated fault detection and diagnosis (AFDD) tools have been developed to address this national issue and many tools are commercially available. AFDD tools have the potential to save considerable energy for existing commercial RTUs, chillers and refrigeration systems. These devices can be used for both retro commissioning, and, when faults are addressed, continuous commissioning as well. However, there appears to be multiple market barriers for this technology. A key market barrier for this technology is the lack of awareness of AFDD products among potential customers. Most HVAC contractors are not familiar with the latest AFDD technologies and HVAC technicians lack skills regarding these technologies. Quantifying potential benefits to building owners is difficult since there are several FDD tools with varying capabilities. For instance, there are several FDD products ranging from handling just economizer faults to those that also handle full-blown refrigerant-side and air-side faults. Methods/algorithms used in FDD vary significantly. Even though there are efforts to develop standards, currently there are no standards/methods to define functions, capabilities, accuracy, and reliability of FDD tools. Moreover, most of the commercial AFDD tools have not been verified in the field independently. This paper presents a comprehensive approach to bringing HVAC AFDD tools into the mainstream. The approach involves demonstrating ten commercially available tools at ten different sites, independent testing and evaluation of the FDD tools, communication with various stakeholders, identifying market barriers, and assisting utility companies in developing incentive programs. This paper presents selection of AFDD tools, ite identification, and field testing and evaluation method.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

First Measurement Of Charged-current 1 Muon 2 Proton 0 Pion Single Differential Cross-sections On Argon-40 At 0.8 Gev Average Neutrino Energy With The MicroBooNE Detector

Constraining systematic uncertainties that arise from neutrino-nucleon cross-section modeling is critical for upcoming neutrino oscillation experiments. Neutrino interactions that lead to the ejection of 2 particles from the target nucleus, leaving the nucleus with 2 holes, are one cross-section of interest. These instances, known as 2-particle 2-hole (2p2h) states, can be produced either by neutrino interaction modes or from the influence of nuclear physics on the neutrino interaction. While there are many theoretical models that attempt to describe the nature of 2p2h states, very few experimental measurements of this process exist, making it difficult to benchmark theoretical calculations. Furthermore, no high statistic cross-section measurements of 2p2h states exist on $^{40}$Ar, the target nucleus of many current and next generation neutrino oscillation experiments. This analysis aims to address this issue by providing the first high-statistic single differential cross-section me asurements of 2p2h states. Using data collected from the first 3 years of running of the MicroBooNE experiment, we select $\nu_\mu$ charged-current interaction events that produce a single muon, 2 protons, and no pions in the final state (CC1$\mu$2p0$\pi$). The single differential cross-section is then extracted as a function of a variety of physics variables and compared to theoretical predictions from several event generator model sets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2008

Making Complex Electrically Conductive Patterns on Cloth

A method for automated fabrication of flexible, electrically conductive patterns on cloth substrates has been demonstrated. Products developed using this method, or related prior methods, are instances of a technology known as 'e-textiles,' in which electrically conductive patterns ar formed in, and on, textiles. For many applications, including high-speed digital circuits, antennas, and radio frequency (RF) circuits, an e-textile method should be capable of providing high surface conductivity, tight tolerances for control of characteristic impedances, and geometrically complex conductive patterns. Unlike prior methods, the present method satisfies all three of these criteria. Typical patterns can include such circuit structures as RF transmission lines, antennas, filters, and other conductive patterns equivalent to those of conventional printed circuits. The present method overcomes the limitations of the prior methods for forming the equivalent of printed circuits on cloth. A typical fabrication process according to the present method involves selecting the appropriate conductive and non-conductive fabric layers to build the e-textile circuit. The present method uses commercially available woven conductive cloth with established surface conductivity specifications. Dielectric constant, loss tangent, and thickness are some of the parameters to be considered for the non-conductive fabric layers. The circuit design of the conductive woven fabric is secured onto a non-conductive fabric layer using sewing, embroidery, and/or adhesive means. The portion of the conductive fabric that is not part of the circuit is next cut from the desired circuit using an automated machine such as a printed-circuit-board milling machine or a laser cutting machine. Fiducials can be used to align the circuit and the cutting machine. Multilayer circuits can be built starting with the inner layer and using conductive thread to make electrical connections between layers.

Chu, Andrew↗
DOE OSTI2022

A deep learning approach to identify missing is-a relations in SNOMED CT

Abstract Objective SNOMED CT is the largest clinical terminology worldwide. Quality assurance of SNOMED CT is of utmost importance to ensure that it provides accurate domain knowledge to various SNOMED CT-based applications. In this work, we introduce a deep learning-based approach to uncover missing is-a relations in SNOMED CT. Materials and Methods Our focus is to identify missing is-a relations between concept-pairs exhibiting a containment pattern (ie, the set of words of one concept being a proper subset of that of the other concept). We use hierarchically related containment concept-pairs as positive instances and hierarchically unrelated containment concept-pairs as negative instances to train a model predicting whether an is-a relation exists between 2 concepts with containment pattern. The model is a binary classifier leveraging concept name features, hierarchical features, enriched lexical attribute features, and logical definition features. We introduce a cross-validation inspired approach to identify missing is-a relations among all hierarchically unrelated containment concept-pairs. Results We trained and applied our model on the Clinical finding subhierarchy of SNOMED CT (September 2019 US edition). Our model (based on the validation sets) achieved a precision of 0.8164, recall of 0.8397, and F1 score of 0.8279. Applying the model to predict actual missing is-a relations, we obtained a total of 1661 potential candidates. Domain experts performed evaluation on randomly selected 230 samples and verified that 192 (83.48%) are valid. Conclusions The results showed that our deep learning approach is effective in uncovering missing is-a relations between containment concept-pairs in SNOMED CT.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2018

Corrosion of Bare Carbon Steel as a Passive Sensor to Assess Moisture Availability for Biological Activity in Atacama Desert Soils

In this work we suggest the corrosion of polished bared metal coupons as a passive sensor to detect or identify the lower limit of water availability that could be suitable for biological activity in the Atacama Desert on soil or solid substrates. For this purpose, carbon steel coupons were deposited in selected sites along a west-east transect and removed at predetermined times for morphological inspection. The advantage of this procedure is that the attributes of the oxide layer (corrosion extent, morphology and oxide phases) can be considered as a fingerprint of the atmospheric moisture history at a given time interval. Two types of coupons were used, a long rectangular shape that are half-buried in a vertical position, and square shape that are deposited on the soil surface. The morphological attributes observed by SEM inspection is correlated to the so-called humectation time which is determined from local meteorological parameters. The main result is that the decreasing trend of atmospheric moisture along the transect is closely related to corrosion behavior and water soil penetration. For instance, while in the coastal site oxide phases formed on the coupon surface rapidly evolve to well- crystallized species, in the driest inland site Lomas Bayas only amorphous oxide is observed.

Caceres, Luis↗
NASA NTRS2014

Transfer of Training on the Vertical Motion Simulator

This paper describes a transfer-of-training study in the NASA Ames Vertical Motion Simulator (VMS). Sixty-one general aviation pilots, divided in four groups, trained on four challenging commercial transport tasks with four motion conditions: no motion, small hexapod, large hexapod, and VMS motion. Then, every pilot repeated the tasks with VMS motion to determine if training with different motion conditions had an effect. New objective motion criteria guided the selection of the motion parameters for the small and large hexapod conditions. Considering results that were statistically significant, or marginally, the motion condition used in training affected 1) longitudinal and lateral touchdown location; 2) the number of secondary stall warnings in a stall recovery; 3) pilot ratings of motion utility and maximum load factor obtained in an overbanked upset recovery; and 4) pilot ratings of motion utility and pedal input reaction time in the engine-out-on-takeoff task. Since the motion condition revealed statistical differences on objective measures in all the tasks, even with some in the direction not predicted, trainers should be cautious not to oversimplify the effects of platform motion. Evidence suggests that the new objective motion criteria may offer valid standardization benefits, as instances arose when the higher-fidelity hexapod motion, as predicted by the criteria, provided better cues in training than the lower-fidelity hexapod motion.

Zaal, Peter M. T.↗
DOE OSTI2019

The spectral energy distributions of active galactic nuclei

ABSTRACT We present spectral energy distributions (SEDs) of 41 active galactic nuclei, derived from multiwavelength photometry and archival spectroscopy. All of the SEDs span at least 0.09 to 30 $\mu$m, but in some instances wavelength coverage extends into the X-ray, far-infrared, and radio. For some active galactic nuclei (AGNs) we have fitted the measured far-infrared photometry with greybody models, while radio flux density measurements have been approximated by power laws or polynomials. We have been able to fill some of the gaps in the spectral coverage using interpolation or extrapolation of simple models. In addition to the 41 individual AGN SEDs, we have produced 72 Seyfert SEDs by mixing SEDs of the central regions of Seyferts with galaxy SEDs. Relative to the literature, our templates have broader wavelength coverage and/or higher spectral resolution. We have tested the utility of our SEDs by using them to generate photometric redshifts for 0 < z ≤ 6.12 AGNs in the Boötes field (selected with X-ray, IR, and optical criteria) and, relative to SEDs from the literature, they produce comparable or better photometric redshifts with reduced flux density residuals.

Brown, M. J. I.↗
DOE OSTI2024

Adaptive Fault Current-Limiting Control of MMC for Protection of Multiterminal HVDC Systems: Preprint

For the development of multi-terminal high voltage DC (MTDC) transmission, it is critical to design the protection system that can selectively isolate the faulty area from the healthy part of the dc grid using DC circuit breakers (DCCBs) while ensuring continuous operation of converter stations in the healthy part. However, because of the lack of fault current blocking capability in half-bridge (HB) modular multilevel converters (MMCs), when a dc fault occurs, the rising fault currents can quickly reach the blocking threshold within a few milliseconds and disrupt the operation of MMCs in the healthy part. Large DC reactors are often considered in series with DCCBs to reduce the rate of rise of fault currents and prevent blocking of MMCs in the healthy part of the grid. However, large DC reactors can prohibitively increase the cost of the system, particularly when they are considered in an offshore environment, for instance in offshore wind projects. Large dc reactors can also introduce stability issues and create post-fault oscillations. This paper presents an adaptive fault current limiting control method for MMCs to avoid their blocking and enable continuous operation of MTDC systems. It contains two parts: The first part is based on circulating current feedforward control that emulates virtual reactors in each arm of an MMC, which is immediately activated when the fault current starts to increase, to reduce the rate of rise of the fault current; the second part is triggered when the fault current exceeds a preset threshold by temporarily bypassing the SMs, serving as a complement to the fault current limiting effect of the first part. Both parts do not require fault detection signal and they are activated automatically during faults. Simulation case studies of a four-terminal bipolar MMC-HVDC system are presented to demonstrate the effectiveness of the proposed control methods.

active fault current limiting↗
DOE OSTI2022

Detecting Cage Crossing and Filling Clusters of Magnesium and Carbon Atoms in Zeolite SSZ-13 with Atom Probe Tomography

The conversion of methanol to valuable hydrocarbon molecules is of great commercial interest, as the process serves as a sustainable alternative for the production of, for instance, the base chemicals for plastics. The reaction is catalyzed by zeolite materials. By the introduction of magnesium as a cationic metal, the properties of the zeolite, and thereby the catalytic performance, are changed. With atom probe tomography (APT), nanoscale relations within zeolite materials can be revealed: i.e., crucial information for a fundamental mechanistic understanding. We show that magnesium forms clusters within the cages of zeolite SSZ-13, while the framework elements are homogeneously distributed. These clusters of just a few nanometers were analyzed and visualized in 3-D. Magnesium atoms seem to initially be directed to the aluminum sites, after which they aggregate and fill one or two cages in the zeolite SSZ-13 structure. The presence of magnesium in zeolite SSZ-13 increases the lifetime as well as the propylene selectivity. By using operando UV–vis spectroscopy and X-ray diffraction techniques, we are able to show that these findings are related to the suppression of aromatic intermediate products, while maintaining the formation of polyaromatic compounds. Further nanoscale analysis of the spent catalysts showed indications of magnesium redistribution after catalysis. Unlike zeolite H-SSZ-13, for which only a homogeneous distribution of carbon was found, carbon can be either homogeneously or heterogeneously distributed within zeolite Mg-SSZ-13 crystals as the magnesium decreases the coking rate. Carbon clusters were isolated, visualized, and analyzed and were assumed to be polyaromatic compounds. Small one-cage-filling polyaromatic compounds were identified; furthermore, large-cage-crossing aromatic molecules were found by isolating large coke clusters, demonstrating the unique coking mechanism in zeolite SSZ-13. Short-length-scale evidence for the formation of polyaromatic compounds at acid sites is discovered, as clear nanoscale relations between aluminum and carbon atoms exist.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2010

Complexity Analysis of Traffic in Corridors-in-the-Sky

The corridors-in-the-sky concept imitates the highway system in ground transportation. The benefit expected from a corridor relies on its capability of handling high density traffic with negligible controller workload, the acceptance of extra fuel or distance, and the complexity reduction in underlying sectors. This work evaluates a selected corridor from these perspectives through simulations. To examine traffic inside the corridor, a corridor traffic simulation tool that can resolve conflicts is developed using C language. Prescribed conflict resolution maneuvers mimic corridor users behaviors and conflict resolution counts measure complexity. Different lane options and operational policies are proposed to examine their impacts on complexity. Fuel consumption is calculated and compared for corridor traffic. On the other hand, to investigate the complexity of non-corridor traffic in underlying sectors, the existing Airspace Concept Evaluation System tool is utilized along with the Automated Airspace Concept tool. The number of conflict resolutions is examined and treated as the complexity measurement. The results show heavy traffic can be managed with low complexity for a historical traffic schedule simulated with appropriate operational policies and lane options. For instance, with 608 flights and peak aircraft count of 100, only 84 actions need to be taken in a 24-hour period to resolve the conflicts for an 8-lane corridor. Compared with the fuel consumptions with great circle trajectories, the simulation of corridor traffic shows that the total extra fuel for corridor flights is 26,373 gallons, or 2.76%, which is 0.38% less than flying filed flight plans. Without taking climb and descent portions of corridor traffic, the complexity of underlying sectors is reduced by 17.71%. However the climb and descent portions will eliminate the reduction and the overall complexity of sectors is actually increased by 9.14%.

Xue, Min↗
NASA NTRS2011

NASA Technology Demonstrations Missions Program Overview

The National Aeronautics and Space Administration (NASA) Fiscal Year 2010 (FY10) budget introduced a new strategic plan that placed renewed emphasis on advanced missions beyond Earth orbit. This supports NASA s 2011 strategic goal to create innovative new space technologies for our exploration, science, and economic future. As a result of this focus on undertaking many and more complex missions, NASA placed its attention on a greater investment in technology development, and this shift resulted in the establishment of the Technology Demonstrations Missions (TDM) Program. The TDM Program, within the newly formed NASA Office of the Chief Technologist, supports NASA s grand challenges by providing a steady cadence of advanced space technology demonstrations (Figure 1), allowing the infusion of flexible path capabilities for future exploration. The TDM Program's goal is to mature crosscutting capabilities to flight readiness in support of multiple future space missions, including flight test projects where demonstration is needed before the capability can transition to direct mission The TDM Program has several unique criteria that set it apart from other NASA program offices. For instance, the TDM Office matures a small number of technologies that are of benefit to multiple customers to flight technology readiness level (TRL) 6 through relevant environment testing on a 3-year development schedule. These technologies must be crosscutting, which is defined as technology with potential to benefit multiple mission directorates, other government agencies, or the aerospace industry, and they must capture significant public interest and awareness. These projects will rely heavily on industry partner collaboration, and funding is capped for all elements of the flight test demonstration including planning, hardware development, software development, launch costs, ground operations, and post-test assessments. In order to inspire collaboration across government and industry, more than 70% of the TDM funds will be competitively awarded as a result of yearly calls for proposed flight demonstrators and selected based on possible payoff to NASA, technology maturity, customer interest, cost, and technical risk reduction. This paper will give an overview of the TDM Program s mission and organization, as well as its current status in delivering advanced space technologies that will enable more flexible and robust future missions. It also will provide several examples of missions that fit within these parameters and expected outcomes.

Turner, Susan↗