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NASA NTRS2018

Real-Time Adaptive Drag Minimization Wind Tunnel Investigation of a Flexible Wing with Variable Camber Continuous Trailing Edge Flap System

This paper reports the results of a recently completed real-time adaptive drag minimization wind tunnel investigation of a highly flexible wing wind tunnel model equipped with the Variable Camber Continuous Trailing Flap (VCCTEF) technology at the University of Washington Aeronautical Laboratory (UWAL). The wind tunnel investigation is funded by NASA SBIR Phase II contract with Scientific Systems Company, Inc. (SSCI) and University of Washington (UW) as a subcontractor. The wind tunnel model is a sub-scale Common Research Model (CRM) wing constructed of foam core and fiberglass skin and is aeroelastically scaled to achieve a wing tip deflection of 10% of the wing semi-span which represents a typical wing tip deflection for a modern transport such as Boeing 787. The jig-shape twist of the CRM wing is optimized using a CART3D aero-structural model to achieve the minimum induced drag for the design cruise lift coefficient of 0.5. The wing is equipped with two chord wise cambered segments for each of the six span wise flap sections for a total of 12 individual flap segments that comprise the VCCTEF system. Each of the 12 flap segments is actively controlled by an electric servo-actuator. The real-time adaptive drag optimization strategy includes an on-board aerodynamic model identification, a model excitation, and a real-time drag optimization. The on-board aerodynamic model is constructed parametrically as a function of the angle of attack and flap positions to model the lift and drag coefficients of the wing. The lift coefficient models include a linear model and a second-order model. The drag coefficient models include a quadratic model and a higher-order up to 6th-order model to accurately model the drag coefficient at high angles of attack. The onboard aerodynamic model identification includes a recursive least-squares (RLS) algorithm and a batch least-squares (BLS) algorithm designed to estimate the model parameters. The model excitation method is designed to sample the input set that comprises the angle of attack and the flap positions. Three model excitation methods are developed: random excitation method, sweep method, and iterative angle-of-attack seeking method. The real-time drag optimization includes a generic algorithm developed by SSCI and several optimization methods developed by NASA which include a second-order gradient Newton-Raphson optimization method, an iterative gradient optimization method, a pseudo-inverse optimization method, an analytical optimization method, and an iterative refinement optimization method. The first wind tunnel test entry took place in September 2017. This test revealed major hardware issues and required further redesign of the flap servo mechanisms. The second test entry took place in April 2018. However, the test was not successful due to the issues with the onboard aerodynamic model identification RLS algorithm which incorrectly identified model parameters. This test also provides an experimental comparison study between the VCCTEF and a variable camber discrete trailing edge flap (VCDTEF) without the elastomer transition mechanisms. The experimental result confirms the benefit of the VCCTEF which produces lower drag by 5% than the VCDTEF. The third and final test entry took place in June 2018 after the issues with the RLS algorithm have been identified and corrected. Additional improvements were implemented. These include the BLS algorithm, the iterative angle-of-attack seeking method, the iterative gradient optimization method, and the pseudo-inverse optimization method. The test objectives were successfully demonstrated as the real-time drag optimization identifies several optimal solutions at off-design lift coefficients. The iterative gradient optimization method is found to achieve up to 4.7% drag reduction for the off-design lift coefficient of 0.7. The pseudo-inverse optimization method which does not require the drag coefficient model is found to be quite effective in reducing drag. Up to 9.4% drag reduction for the off-design lift coefficient of 0.7 is achieved with the pseudo-inverse optimization method. The wind tunnel investigation demonstrates the potential of real-time drag optimization technology. Several new capabilities are developed that could enable future adaptive wing technologies for flexible wings equipped with drag control devices such as the VCCTEF.

Drag Optimization↗
NASA NTRS2018

Shifting Data Collection from a Fixed to an Adaptive Sampling Paradigm

For domains where data are difficult to obtain due to human or resource limitations, an emphasis is needed to efficiently explore the dimensions of information spaces to acquire any given response of interest. Many disciplines are still making the transition from brute force, dense, full factorial exploration of their information spaces to a more efficient design of experiments approach; the latter being in use successfully for many decades in agricultural and automotive applications. Although this transition is still incomplete, groundwork must be laid for incorporating the next generation of algorithms to adaptively explore the information space in response to data collected, as well as any resulting empirical models (i.e., metamodels). The methodology in the present work was to compare metamodel quality using a fixed sampling technique compared to an adaptive sampling technique based on metamodel variance. In order to quantify metamodeling errors, a delta method was used to provide quantitative model variance estimates. The present methodology was applied to a design space with an air-breathing engine performance response. It was shown that competitive metamodel quality with lower associated error could be achieved for an adaptive sampling technique for the same level of effort as a fixed, a priori sampling technique.

Axdahl, Erik L.↗
NASA NTRSDate not supplied

Exploring Unstructured Mesh Adaptation for Hybrid Reynolds-Averaged Navier–Stokes/Large Eddy Simulation

Mesh adaptation methods for the Reynolds-averaged Navier–Stokes (RANS) equations are rapidly maturing and beginning to impact the design of aerospace vehicles. RANS turbulence modeling improvements have slowed and may stagnate. Wall-modeled large eddy simulation (LES) and hybrid RANS/LES (HRLES) may provide an improved modeling capability but require specialized expertise to construct appropriate meshes and are considered be too ex-pensive for routine practical use. The realization of the CFD Vision 2030 Study includes improving geometry linkage, mesh generation/adaptation, and turbulence modeling/resolving methods for automated management of errors and uncertainties of physics-based, predictive modeling that can set the stage for ensuring a vehicle is in compliance with a regulation or specification (i.e., certification or qualification by analysis). An exploration of mesh adaptation for HRLES is performed to document synergies and challenges between mesh adaptation and HRLES. Vortex breakdown over a delta wing is examined to show the improvement of HRLES over RANS turbulence modeling approaches. A high lift configuration is shown to demonstrate complex geometry capability. Research and development opportunities are identified to advocate for continuing investments that may allow HRLES to enter routine practical use as a tool for aerospace vehicle analysis and design.

Michael A Park↗
NASA NTRSDate not supplied

Adaptive Pressure Profile Method to Locate the Isolator Shock Train Leading Edge Given Limited Pressure Information

To maximize the performance of high-speed air-breathing engines, such as dual-mode scramjets, the streamwise location of the shock train leading edge (STLE) is ideally placed as far upstream in the isolator as possible while avoiding engine unstart. Thus, it is of interest to quantify and control the STLE location as the vehicle travels along its flight trajectory. The STLE location is typically quantified using wall static pressure measurements but there are often restrictions on the number and placement of transducers, thus reducing the accuracy and overall capability of STLE detection methods. In this work, the Adaptive Pressure Profile (APP) method is introduced to address such sparsity concerns. This method is data driven and does not heavily rely on prior information about the flow regime or engine model. Instead, the \mname method uses real-time pressure measurements from a small number of transducers to adaptively learn the isolator pressure profile. This adaptively-learned profile is fit to the pressure data at each time instance to estimate STLE location. The \mname method produces accurate estimates even when (1) the STLE location is not bounded by two or more transducers or (2) when the STLE location is between two transducers that are situated several duct heights apart. Data from two direct-connect isolator models are used to evaluate the accuracy of the \mname method and demonstrate its robustness for different back-pressure scenarios and transducer configurations.

Robin L Hunt↗
NASA NTRSDate not supplied

Adaptive Pressure Profile Method to Locate the Isolator Shock Train Leading Edge Given Limited Pressure Information

To maximize the performance of high-speed air-breathing engines, such as dual-mode scramjets, the streamwise location of the shock train leading edge (STLE) is ideally placed as far upstream in the isolator as possible while avoiding engine unstart. Thus, it is of interest to quantify and control the STLE location as the vehicle travels along its flight trajectory. The STLE location is typically quantified using wall static pressure measurements but there are often restrictions on the number and placement of transducers, thus reducing the accuracy and overall capability of STLE detection methods. In this work, the Adaptive Pressure Profile (APP) method is introduced to address such sparsity concerns. This method is data driven and does not heavily rely on prior information about the flow regime or engine model. Instead, the \mname method uses real-time pressure measurements from a small number of transducers to adaptively learn the isolator pressure profile. This adaptively-learned profile is fit to the pressure data at each time instance to estimate STLE location. The \mname method produces accurate estimates even when (1) the STLE location is not bounded by two or more transducers or (2) when the STLE location is between two transducers that are situated several duct heights apart. Data from two direct-connect isolator models are used to evaluate the accuracy of the \mname method and demonstrate its robustness for different back-pressure scenarios and transducer configurations.

Robin Hunt↗
NASA NTRS1994

Stable Direct Adaptive Periodic Control Using Only Plant Order Knowledge

The main contribution of this paper is to put stability requirements for convergence of direct adaptive periodic controllers on equal footing with requirements for indirect adaptive periodic control, as set forth by Lozano. The resulting stability condition is simply that the plant order is known a priori. No other prior plant knowledge is used (e.g., relative degree, high-frequency gain, etc.), and persistent excitation is not required. More importantly, no assumption or knowledge is required as to whether the plant is minimum or nonminimum phase. A numerical example is given to demonstrate the method, and some guidelines are given for improving the adaptive transient response.

sampling↗
NASA NTRS2021

Adaptive Aerostructures for Revolutionary Civil Supersonic Transportation

To enable commercially viable civil supersonic transport (SST) aircraft, innovative solutions must be developed to meet noise and efficiency requirements for overland flight. This research effort consists of a multidisciplinary team of academic and industrial experts exploring for the first time the potential of small real-time geometric outer mold line (OML) reconfigurations to minimize sonic boom signatures and aircraft drag in response to changing ambient conditions, thereby enabling noise-compliant overland supersonic flight. The team utilizes recent advances in supersonic computational fluid dynamic (CFD) methods, new noise prediction tools, and new design approaches to consider embedded highly energy-dense shape memory alloy (SMA) actuators for local shape modifications to an SST aircraft leading to optimal low boom signature and low drag in different environments. This university-led program will provide strategic leadership toward technology convergence that advances NASA's Aerospace Research Mission Directorate's (ARMD) research objectives with regard to Thrust 2: “Innovation in Commercial Supersonic Aircraft” by exploring for the first time enabling low-boom operation across a range of flight conditions via structural adaptivity, and will promote education of the next generation of engineers. The overall research strategy is to pursue three critical areas: the design of configurations for reducing boom, SMA material development and modeling, and technology feasibility demonstration in a relevant environment. Initially, the team will identify potential applications where structure or geometry adaptivity provides a benefit in noise or drag across the entire flight envelope. For selected applications/structural locations, required OML geometry changes will be determined based on analysis of sonic boom ground signature and drag reduction using new design tools, trade studies, and atmospheric sensing techniques. Designs will be developed and evaluated against requirements on loading, stroke length, and operational temperature. New alloy formulations will be developed tailored for both autonomous and controlled actuation modes. As the SMA material development matures, integrated system-level factors will be investigated. Optimized designs for small-scale distributed adaptivity applications of maximum benefit will then be matured and tested, moving toward demonstration of the innovative technology approaches at a TRL 4-5 and showing that sonic booms can be reduced by reconfiguration on demand.

Koushik Datta↗
NASA NTRSDate not supplied

Enterococci in Space: Adaptation, Antibiotic Resistance, and Clinical Implications

Enterococci are gram-positive bacteria that originated when our ancient animal ancestors emerged from the oceans to live on land, and brought their gut flora with them. Enterococcus faecalis (EF) and Enterococcus faecium, are common human commensals and can harbor multidrug resistance. Both have been previously isolated from the International Space Station (ISS). Likely as a consequence of their evolutionary origins, enterococci show remarkable stress resistance within, but also outside, their human hosts. Their antibiotic resistance, coupled with tolerance to desiccation, starvation, and disinfection, make some EF strains potent pathogens in the built environment (e.g., hospitals), and a potential risk to crew health during space missions. Here we describe our planned flight studies, currently in development. Genomic Enumeration of Antibiotic Resistance in Space (GEARS) will characterize the frequency and genomic identity of antibiotic resistant organisms, including enterococci, on the ISS, and expand our future in-space sequencing-based diagnostic capabilities. Enterococcus Growth Advantage on ISS via Tn-seq (EnteroGAIT) will assess the evolutionary selective pressure of the space environment (microgravity, space radiation) using EF as a model system during a long-duration culture and persistence experiment. Adaptation & Evolution of Resilient Enterococcus in Space (AERES) will study existing and newly identified isolates to characterize the “natural” evolutionary history of EF on Earth and in space to reveal mechanisms of microbial adaption including, possibly, natural selection. Our work to date has identified that EF ISS isolates share virulence factors found in clinical strains and commensals, and revealed limitations of current pathogenicity assessment tools. While ISS isolates were, in some cases, multi-drug resistant, current data suggests these are largely commensal strains. Our work will further refine potential crew health risks and improve understanding of EF adaptation to the built environment, of great relevance on Earth where EF is the second leading cause of hospital acquired infection.

Jordan McKaig↗
NASA NTRSDate not supplied

NSCOR for Evaluating Risk Factors and Biomarkers for Adaptation and Resilience to Spaceflight: Emotional Valence and Social Processes in ICC/ICE Environments

Space exploration class missions, such as a mission to Mars, will require optimization of human performance, adaptability, and resilience. This NASA Specialized Center of Research (NSCOR) utilizes the NIMH Research Domain Criteria (RDoC) framework to identify biological and behavioral markers of individual social adaptation and emotional resilience (as well as vulnerability) to spaceflight-relevant stressors such as living in extended isolation. The overarching goal of this NSCOR is to obtain novel information to help identify biomarkers of individuals who are resilient and/or adaptable to the stressors of isolated, confined, and controlled (ICC) and isolated, confined, and extreme (ICE) environments.A total of N=90 healthy adult astronaut surrogates are being studied in three spaceflight-analog environments: (1) n=40 healthy adults in the Isolation and Confinement Analog Research Unit (ICARUS), an ICC at the University of Pennsylvania, during 7-day missions, for a target total of 280 subject days; (2) n=32 healthy adult astronaut surrogates studied in NASA’s Human Exploration Research Analog (HERA), an ICC at Johnson Space Center during 45-day missions, for a target total of 2,112 subject days; and (3) n=18 healthy adults in the Alfred-Wegener-Institute’s Neumayer Station III, an ICE in Antarctica, during 14-month missions, for a target total of 7,560 subject days. Dr. Nindl’s Laboratory at the University of Pittsburgh is analyzing a priori selected protein biomarkers in blood, saliva, and urine. Complementary rodent models of exposure to early life stressors, confinement, and isolation are being evaluated at Dr. Hensch’s Laboratory to further validate the neurobehavioral and biological findings from the human studies.Given the inconsistency and varied definition of resilience/adaptation in the scientific literature, the NSCOR team developed a composite resilience/adaptation measure that reflects the most relevant outcomes to resilience/adaptation across psychosocial and neurobehavioral functions, as well as neurocognitive and spaceflight-relevant operational performance. To achieve this, group consensus was attained from subject matter experts to produce a rank-order of importance for each input variable. The final resilience/adaptation score included 36 variables that were collected across spaceflight analogs. As of 10/1/2021, the NSCOR project acquired data on n=27 subjects at ICARUS, n=16 at HERA, and n=18 at Neumayer. The COVID-19 pandemic delayed data acquisition at ICARUS and HERA.Among subjects studied to date, 99% of neural and neurobehavioral data (e.g., neuroimaging for structure and function, behavioral measures) as well as blood, saliva, and urine for biochemical assays have been acquired. For rodent models, Dr. Hensch’s laboratory has established biochemical and behavioral parameters reflecting confinement stress in social networks of mice for comparison to stress responses in the human spaceflight analog environments.Group social behaviors were measured with a Social Network Analysis (SNA) approach to define objective parameters associated with sociability and its plasticity by sex. This analytic approach may help identify a network of individuals who are more effective teammates or more likely to generate new social relationships. Data acquisition, biomarker assessment, and data quality control will continue through September 2022.

D F Dinges↗
NASA NTRS2022

Adaptation to environmental extremes structures functional traits in biological soil crust and hypolithic microbial communities

Biological soil crusts (biocrusts) are widespread in drylands and deserts. At the microhabitat scale, they also host hypolithic communities that live under semi-translucent stones. Both environmental niches experience exposure to extreme conditions such as high UV radiation, desiccation, temperature fluctuations, and resource limitation. However, hypolithic communities are somewhat protected from extremes relative to biocrust communities. Conditions are otherwise similar, so comparing them can answer outstanding questions regarding adaptations to environmental extremes. Using metagenomic sequencing, we assessed the functional potential of dryland soil communities and identified the functional underpinnings of ecological niche differentiation in biocrusts versus hypoliths. We also determined the effect of the anchoring photoautotroph (moss or cyanobacteria). Genes and pathways differing in abundance between biocrusts and hypoliths indicate that biocrust communities adapt to the higher levels of UV radiation, desiccation, and temperature extremes through an increased ability to repair damaged DNA, sense and respond to environmental stimuli, and interact with other community members and the environment. Intracellular competition appears to be crucial to both communities, with biocrust communities waging war using the Type VI Secretion System (T6SS) and hypoliths favoring diversity of antibiotics. The dominant primary producer had a reduced effect on community functional potential compared with niche, but an abundance of genes related to monosaccharide, amino acid, and osmoprotectant uptake in moss-dominated communities indicates reliance on resources provided to heterotrophs by mosses. Our findings indicate that functional traits in dryland communities are driven by adaptations to extremes and we identify strategies that likely enable survival in dryland ecosystems.

Biological soil crusts↗
NASA NTRS2022

Adaptive IV&V for Increasingly Complex Software Systems

As NASA software systems continue to innovate, becoming more complex and nondeterministic, the need for the NASA IV&V Program to become systemically adaptive to ensure mission success is paramount. To ensure adaptability within resource constraints, IV&V has developed an agile, risk-based approach to identify, characterize, scope, focus, and prioritize mission assurance activities. This risk based adaptive framework has been applied to trends such as increased reliance on data driven algorithms for safety and mission critical software behavior, use of MBSE in system design, and application of agile principles to embedded software development. The framework is enabled by continuous innovation of new approaches such as software only test beds, assurance design tools, and initiatives that augment IV&V assurance methods with artificial intelligence and machine learning techniques. This presentation will highlight the trends the NASA IV&V Program is seeing, the innovative steps it is taking to address those challenges, and how it is postured to address evolving risk and constantly changing and new technologies.

Wesley W Deadrick↗
NASA NTRS2021

Adaptive-Sweep Algorithm for Spacecraft Carrier Acquisition and Tracking: System Analysis and Implementation

This paper presents an adaptive-sweep algorithm that can be used in conjunction with a Phased-Lock Loop to acquire and track the carrier of a Binary Phase-shift Keying signal with residual carrier. This algorithm is useful in proximity links where no Doppler pre-compensation is available at the transmitter, and allows the receiver to acquire the incoming carrier even if the experienced Doppler shift is several orders of magnitude larger than the PLL bandwidth. Other applications for this algorithm include Multiple Uplink per Antenna at the Deep Space Network, and generation of observables (Doppler shift, Doppler rate, range rate) for in-situ navigation purposes. This paper enhances a previously presented adaptive-sweep algorithm and its performance analysis in two fronts. First, the algorithm now uses the direction function to automatically estimate the required frequency jump to achieve PLL lock. This enables a fully adaptive-sweep scheme in which system implementer does not need to manually select thresholds. On the other hand, we study the system performance in the presence of Additive White Gaussian Noise and derive necessary conditions for the system to operate at low signal-to-noise conditions. This allows us to create design rules that specify all parameters of the algorithm given a set of system-level requirements. To test the performance of the proposed algorithm, we implement it in GNU Radio, an open-source Software-Defined Radio that interfaces with several commercial radio peripherals. We use this implementation to demonstrate carrier lock and quantify system performance under different noise conditions. We also test the algorithm using open-loop recordings of two downlinks between the Lunar Reconnaissance Orbiter and the Deep Space Network. We show that even after large frequency jumps (tens of kHz), the proposed system is able to rapidly reacquire the carrier and continue operation.

Divsalar, Dariush↗
NASA NTRSDate not supplied

Adaptative Site Management for a 115 Acre Chlorinated Solvent Plume with Two Separate Source Areas at Kennedy Space Center, Florida

Background/Objectives. During Resource Conservation and Recovery Act (RCRA) Facility Investigation (RFI) activities, Geosyntec delineated a chlorinated volatile organic compound (CVOC) plume at the National Aeronautics and Space Administration’s (NASA’s) Vehicle Assembly Building (VAB) area located at KSC, Florida. The RFI activities identified an approximate 115-acre dissolved plume (primarily vinyl chloride) and a trichloroethene (TCE) source area in an active aerospace complex that is surrounded by sensitive wetland/waterbodies. Due to the size of the impacted area, the Corrective Measure Design included a multi-component strategy: (i) address the source area via bioremediation; (ii) protect sensitive wetlands from impacted groundwater discharge via biosparging; and (iii) Long Term Monitoring (LTM) of the remaining dissolved plume. After the Corrective Measures implementation (CMI), NASA and Geosyntec worked with Florida Department of Environmental Protection (FDEP) to implement an adaptive site management for the complex, 115-acre site outside of the traditional RCRA process. The adaptive site management approach relied on performing supplemental assessments and implementing Interim Measures (IMs) to further assess and implement remedies over time while working within site and budget constraints, with an overall goal of achieving enough mass reduction to transition the entire site to LTM and eventually achieve site closure. Approach/Activities. After the biosparge barrier was operational and bioremediation within the source area (referred to as Hot Spot 1) achieved the Corrective Action Objective (CAO), supplemental assessment of the area between Hot Spot 1 and the biosparge barrier was performed. The conceptual site model was updated using the supplemental assessment results and an air sparge system IM was designed to treat an approximate 1.2 acre area (referred to as Hot Spot 2). After installation of the air sparge system, supplemental assessment within the remainder of the 115-acre dissolved plume was performed and a second TCE source area was identified. The TCE source area and associated areas with elevated CVOC concentrations (referred to as Hot Spot 3) were delineated and a bioremediation IM was implemented. Also, the downgradient impacts from Hot Spot 3 were adjacent to a sensitive waterbody, and negotiations with the FDEP allowed the area to be monitored using LTM. Results/Lessons Learned. The performance of supplemental assessment activities and implementation of remedial alternatives as IMs allowed NASA to successfully address groundwater impacts over time, while working within the FDEP regulatory framework. The implementation of the CMI and multiple IMs has achieved the following goals: (i) the biosparge barrier has mitigated the potential discharge of impacted groundwater to an adjacent wetland; (ii) enhanced bioremediation within Hot Spot 1 achieved the CAO within 2 years and transitioned the area into LTM; (iii) operation of an air sparge system within Hot Spot 2 removed TCE as a constituent of concern and contributed to a reduction (approximately 43%) in the impacted groundwater area outside the air sparge treatment area (plume collapse); and (iv) bioremediation within Hot Spot 3 removed approximately 80% of the CVOC mass and contributed to a reduction (approximately 47%) in the impacted groundwater area outside the bioremediation IM treatment area. Overall, the adaptive approach is protecting the sensitive water bodies surrounding the complex site and reducing the area of impacted groundwater, which is moving the entire site towards LTM.

Rebecca C Daprato↗
NASA NTRS2022

Mechanically Tunable Radiative Cooling for Adaptive Thermal Control

Passive radiative cooling is currently thefrontier technology in renewable-energy research. Interms of extraterrestrial applications, radiative cooling is a critical component to the thermalmanagement system of a spacecraft, where the extreme environment of space can cause largetemperature variations that can break and damage equipment. For terrestrial applications,nocturnal or daytime radiative cooling is expected to lead to cost-effective passive heatmanagement without the need of inefficient and costly artificial refrigeration technologies.However, most currently available radiative cooling systems cannot be changed dynamically andradiate a constant static amount of thermal power. Dynamically tunable adaptive radiativecooling systems will be a critical development to prolong the lifetime of spacecraft or improvethe efficiency of terrestrial cooling systems. Here we propose stretchable radiative coolingdesigns that can be substantially tuned by using the simple physical mechanism of mechanical strain. When their structure is stretched, the radiated power is significantly reduced. We developa modeling method that can simulate mechanical stretching combined with electromagnetic response to compute the tunable thermal emission of these new adaptive radiative coolingsystems. The presented photonically engineered structures can be used as coatings to achieveefficient adaptive thermal control of various objects in a cost-effective and environmentallyfriendly way. The proposed designs are much simpler to be realized than others found in theliterature and the best design achieves a high thermal emission power with a tunable range on theorder of 132 W/m2.

Andrew Butler↗
NASA NTRS2022

Adaptive Force Control for Small Celestial Body Sampling

An adaptive force control algorithm for small celestial body sampling for a variety of surface properties is developed. The control algorithm consists of an adaptive controller combined with feedback linearization. When a spacecraft makes contact with the surface, it must maintain a desired contact force in order to capture a sample. The properties of the surface are unknown or uncertain before contact with the surface is made. The adaptive controller performs system identification online to create an input-output model of the feedback linearized system. From the input-output model a block observable canonical form is realized and the control input is determined by model predictive control (MPC) to maintain a desired contact force in spite of the unknown surface properties. The approach is applied to a variety of surface properties with linear and nonlinear contact models.

Quadrelli, Marco M↗
NASA NTRS2022

The NEID Port Adapter on-Sky Performance

Here we detail the on-sky performance of the NEID Port Adapter one year into full science operation at the WIYN 3.5m Telescope at Kitt Peak National Observatory. NEID is an optical (380-930 nm), fiber-fed, precision Doppler radial velocity system developed as part of the NASA-NSF Exoplanet Observational Research (NN-EXPLORE) partnership. The NEID Port Adapter mounts directly to a bent-Cassegrain port on the WIYN Telescope and is responsible for precisely and stably placing target light on the science fibers. Precision acquisition and guiding is a critical component of such extreme precision spectrographs. In this work, we describe key on-sky performance results compared to initial design requirements and error budgets. While the current Port Adapter performance is more than sufficient for the NEID system to achieve and indeed exceed its formal instrumental radial velocity precision requirements, we continue to characterize and further optimize its performance and efficiency. This enables us to obtain better NEID datasets and in some cases, improve the performance of key terms in the error budget needed for future extreme precision spectrographs with the goal of observing ExoEarths, requiring ∼ 10 cm/s radial velocity measurements.

Sarah E. Logsdon↗
NASA NTRSDate not supplied

Incorporating ADAPT-VQE with a Sparse Wavefunction Circuit Simulator to Find Compact Quantum Circuits for Chemical Applications

We implemented the ADAPT-VQE algorithm into our recent classical sparse wavefunction circuit simulator to demonstrate that classical resources can (1) efficiently find a physically motivated compact wavefunction ansatz for further refinement on near-term quantum hardware and (2) benchmark expected results of VQE-based algorithms once the quantum hardware is available to study large-scale applications. In particular, we study the role of the ADAPT-VQE operator pool, molecular basis set selection, and variations such as TETRIS-ADAPT-VQE on the performance of our classical circuit simulator. This work demonstrates the promise of using classical resources to generate highly accurate wavefunctions that can be prepared on quantum hardware to initiate other quantum algorithms such as phase estimation. Our approach harnesses the power of high-performance computing resources with the more limited available quantum computers to map a path toward quantum advantage for electronic structure calculations in chemistry and materials science.

Quantum Computing↗
NASA NTRSDate not supplied

Derivatives Across Adaptive-Step Integration Accurately and Efficiently

The numerical integration of ordinary differential equations (ODEs) is common in trajectory optimization. Previous studies have shown that the use of adaptive-step Runge-Kutta integration schemes can introduce errors in the derivatives due to non-differentiable behavior within the integration scheme itself. The authors previously demonstrated the use of an implicit adaptation to the Runge-Kutta methods to mitigate this issue, but at a significant computational cost. In this work, the authors demonstrate an explicit adaptation to the Runge-Kutta methods to address the issue that does not incur a significant computational cost.

Kaushik Ponnapalli↗