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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Considerations for Improving the Capacity and Performance of AeroMACS

The Aeronautical Mobile Airport Communications System (AeroMACS) has progressed from concept through prototype development, testing, and standards development and is now poised for the first operational deployments at nine US airports by the Federal Aviation Administration. These initial deployments will support fixed applications. Mobile applications providing connectivity to and from aircraft and ground-based vehicles on the airport surface will occur at some point in the future. Given that many fixed applications are possible for AeroMACS, it is necessary to now consider whether the existing capacity of AeroMACS will be reached even before the mobile applications are ready to be added, since AeroMACS is constrained by both available bandwidth and transmit power limitations. This paper describes some concepts that may be applied to improve the future capacity of AeroMACS, with a particular emphasis on gains that can be derived from the addition of IEEE 802.16j multihop relays to the AeroMACS standard, where a significant analysis effort has been undertaken.

radiofrequency spectrum↗
DOE OSTI2024

Reformulation of dicamba herbicide: Impacts on offsite transport and soybean damage

Abstract The herbicide dicamba (3,6‐dichloro‐2‐methoxybenzoic acid) is commonly used to control broadleaf weeds in soybeans. Dicamba, however, is susceptible to volatilization and drift, thereby causing significant plant damage to nontarget crops downwind. Dicamba was reformulated to reduce volatility and off‐target movement. The effectiveness of the dicamba reformulation was assessed by quantifying dicamba emissions following spray application and investigated how meteorological factors influenced the off‐target movement. The experiments were conducted at the University of Minnesota Agricultural Experiment Station (UMORE Park) during the growing season of 2018, 2019, 2021, and 2022. Multiple high‐flow polyurethane foam air samplers were used to measure dicamba concentrations downwind from a 4‐ha soybean field sprayed with dicamba. Dicamba emissions were estimated using backward Lagrangian modeling constrained by the air sample observations. The results indicate that dicamba emissions and downwind transport were significant for several days following application. Further, non‐traited soybeans located within 15–45 m showed substantial dicamba‐related damage. In warmer, drier seasons, increased dicamba emissions caused more severe damage to downwind soybeans, likely worsened by drought stress preventing recovery. Favorable atmospheric conditions that reduced potential drift can be difficult to achieve in terms of the typical weather experienced over agricultural sites in the Upper Midwest. These results indicate that the dicamba reformulation has not adequately prevented significant post‐spray volatilization losses and downwind transport.

Agriculture↗
DOE OSTI2022

Performance and Total Cost of Ownership of a Fuel Cell Hybrid Mining Truck

The main objective of this work was to investigate the potential of hydrogen and fuel cells replacing diesel and internal combustion engines in the ultraclass haul trucks deployed in the mining sector. Performance, range, durability, and cost are the main criteria considered for comparing the two fuels and engine options. Fuel cell system (FCS) performance is characterized in terms of heat rejection, efficiency, and fuel consumption for a hybrid platform equivalent to a 3500 hp diesel engine operating on a representative open pit mining duty cycle. A hybrid platform was chosen because the heat rejection, with a constrained radiator frontal area, limits the maximum fuel cell-rated power by about 50% compared to that of the diesel truck. The hybrid powertrain was 81–88% more efficient than the diesel powertrain on the truck duty cycle. A liquid hydrogen storage system is required for an equal range or time between refilling, but the packaging remains a challenge. Fuel cell and battery durability were evaluated for their performance degradation and lifetime. Achieving a fuel cell lifetime comparable to the time between major overhauls for diesel trucks necessitates the oversizing of the membrane-active area, catalyst overloading, and voltage clipping. For an equal lifetime, the battery must be oversized to control its depth of discharge and charge/discharge rates. A total cost of ownership (TCO) analysis considering the initial capital expenditures, as well as the lifetime cost of fuel, operation, and maintenance, indicates that fuel cells and hydrogen can compete with diesel. A breakeven fuel cost for TCO parity is obtained if H2 is available at USD 5.79–6.85/kg vs. diesel at USD 3.25/gal and the FCS-specific cost is USD 323/kW e relative to USD 250/kW for a diesel genset. Volume manufacturing is required for FCS cost reduction. High volume is possible through the standardization, modularity, and proliferation of class 8 long-haul truck systems across different heavy-duty applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2007

Aeroelastic Model Structure Computation for Envelope Expansion

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear aeroelastic systems. The LASSO minimises the residual sum of squares by the addition of an l(sub 1) penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 Active Aeroelastic Wing using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

Kukreja, Sunil L.↗
NASA NTRS2011

Non-Contact Thermal Properties Measurement with Low-Power Laser and IR Camera System

As shown by the Phoenix Mars Lander's Thermal and Electrical Conductivity Probe (TECP), contact measurements of thermal conductivity and diffusivity (using a modified flux-plate or line-source heat-pulse method) are constrained by a number of factors. Robotic resources must be used to place the probe, making them unavailable for other operations for the duration of the measurement. The range of placement is also limited by mobility, particularly in the case of a lander. Placement is also subject to irregularities in contact quality, resulting in non-repeatable heat transfer to the material under test. Most important from a scientific perspective, the varieties of materials which can be measured are limited to unconsolidated or weakly-cohesive regolith materials, rocks, and ices being too hard for nominal insertion strengths. Accurately measuring thermal properties in the laboratory requires significant experimental finesse, involving sample preparation, controlled and repeatable procedures, and, practically, instrumentation much more voluminous than the sample being tested (heater plates, insulation, temperature sensors). Remote measurements (infrared images from orbiting spacecraft) can reveal composite properties like thermal inertia, but suffer both from a large footprint (low spatial resolution) and convolution of the thermal properties of a potentially layered medium. In situ measurement techniques (the Phoenix TECP is the only robotic measurement of thermal properties to date) suffer from problems of placement range, placement quality, occupation of robotic resources, and the ability to only measure materials of low mechanical strength. A spacecraft needs the ability to perform a non-contact thermal properties measurement in situ. Essential components include low power consumption, leveraging of existing or highly-developed flight technologies, and mechanical simplicity. This new in situ method, by virtue of its being non-contact, bypasses all of these problems. The use of photons to both excite and measure the thermal response of any surface material to a high resolution (estimated footprint = 10 square centimeters) is a generational leap in physical properties measurements. The proposed method consists of spot-heating the surface of a material with a low (less than 1 W) power laser. This produces a moderate (5-10 K) temperature increase in the material.

Hudson, Troy L.↗
NASA NTRSDate not supplied

NASA's Moon to Mars Autonomous Habitat Status

NASA is developing a strategy for sending humans to the Mars vicinity, known broadly as the Moon to Mars (M2M) Campaign. A critical part of this campaign is the development of in-space and surface habitation systems capable of substantially extending human presence beyond Low Earth Orbit (LEO). Mars missions feature an in-space transit habitat capable of supporting crews of four on ~850-1200-day missions, including transit to and from Mars and time in Mars orbit. Surface and transit habitats are complex elements which must keep crewmembers healthy and productive in deep-space environments with limited resources, long rescue times in contingency situations, and communication delays; all within constrained mass, volume, and power budgets. These habitats provide crew both living and workspace as well as most of the resources needed to support crew life. For deep space habitats, automation needs to be employed due to latency and for significant amounts of time when the habitats are uncrewed. Automation of systems is possible in space applications, but there are limitations. Outside of the Earth’s (or any) magnetosphere, radiation environments are harsh to both the physical hardware and the software components. Radiation (charged particles and ionizing electromagnetic waves) degrades and damages the hardware and causes single event upsets (SEUs) in software. If the hardware is damaged, data can be lost, or control actions not made. For software, SEUs cause algorithms to result in different solutions, or incorrect commands to be sent out. This means that algorithms and hardware used for deep space systems are different than what is used on Earth. Radiation-tolerant hardware is generations behind the current state-of-the-art hardware. Recent NASA missions, such as James Webb Space Telescope, continue to rely on older technologies such as the RAD750 processor, and the most advanced processors are still single core and less than 1.5 GHz. There have been attempts to use higher performance processors, but these often take multiple mitigation steps to handle the radiation environments, which limits the processing power and/or throughput. Current techniques for radiation mitigation have been redundancies, voting, physical separation of hardware, encasing materials, under-clocking hardware, and more. Some radiation mitigation techniques do provide benefits such as having a redundant system to improve the probability that a system will be available when needed. Autonomous software systems will have fewer interactions with humans on deep space missions and therefore need to be able to handle more off-nominal conditions. Microgravity also complicates the autonomous aspects of the mission because autonomous systems are usually built from known deterministic states, but microgravity causes physical objects to shift and move changing the location an autonomous system placed the object. Not only does the software need to be reliable and deterministic, losing resources due to a software error is not only costly but detrimental to reputation. The combination of having lower performance hardware and having to be able to verify and deterministically run software and an ever-changing environment makes deep space autonomous systems more complicated. Multiple gaps have been identified including verification of autonomous software algorithms (including artificial intelligence and machine learning), higher performance processors (graphics and general purpose), high speed networks (onboard and transmissions), memory, power distribution, data security, and variations from these. These gaps need to be closed for more advanced systems to be deployed and reduce the size, weight, and power impacts on the habitats.

Scott B. Tashakkor↗
DOE OSTI2020

Microscopic force driving the photoinduced ultrafast phase transition: Time-dependent density functional theory simulations of IrTe 2

Photoinduced phase transitions can have complex and intriguing behaviors more than material ground-state dynamics. Understanding the underlying mechanism can help us to design new ways to manipulate the materials. A variety of mechanisms has been proposed to explain the photoinduced phase transitions of IrTe 2 , but a consensus has yet to be reached. Here, we study the photo-induced phase transitions of IrTe 2 by performing the real-time time-dependent density functional theory (rt-TDDFT) simulations in combination with the occupation constrained DFT method. We reveal that the microscopic driving force for the photo-induced phase transitions arises from the tendency to lower the energy levels occupied by the excited carriers, through the increase or decrease of the associated atomic pair distances, depending on whether the newly occupied states are antibonding or bonding states, respectively. The geometric constraints between different bonds represented by the Poisson ratio can bring together different tendencies from different atomic pairs, thus forming a complex intriguing dynamic picture depending on the intensity of the excitation. Furthermore, we also find that phonons don't play a primary role, but can assist the phase transition. These findings imply that one can control the structural phase transitions by selectively exciting photocarriers into designated atomic states using appropriate photon sources.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗
NASA NTRS1993

A global approach to kinematic path planning to robots with holonomic and nonholonomic constraints

Robots in applications may be subject to holonomic or nonholonomic constraints. Examples of holonomic constraints include a manipulator constrained through the contact with the environment, e.g., inserting a part, turning a crank, etc., and multiple manipulators constrained through a common payload. Examples of nonholonomic constraints include no-slip constraints on mobile robot wheels, local normal rotation constraints for soft finger and rolling contacts in grasping, and conservation of angular momentum of in-orbit space robots. The above examples all involve equality constraints; in applications, there are usually additional inequality constraints such as robot joint limits, self collision and environment collision avoidance constraints, steering angle constraints in mobile robots, etc. The problem of finding a kinematically feasible path that satisfies a given set of holonomic and nonholonomic constraints, of both equality and inequality types is addressed. The path planning problem is first posed as a finite time nonlinear control problem. This problem is subsequently transformed to a static root finding problem in an augmented space which can then be iteratively solved. The algorithm has shown promising results in planning feasible paths for redundant arms satisfying Cartesian path following and goal endpoint specifications, and mobile vehicles with multiple trailers. In contrast to local approaches, this algorithm is less prone to problems such as singularities and local minima.

Divelbiss, Adam↗
DOE OSTI2021

Representations of Precipitation Diurnal Cycle in the Amazon as Simulated by Observationally Constrained Cloud‐System Resolving and Global Climate Models

Abstract The ability of an observationally‐constrained cloud‐system resolving model (Weather Research and Forecasting; WRF, 4‐km grid spacing) and a global climate model (Energy Exascale Earth System Model; E3SM, 1‐degree grid spacing) to represent the precipitation diurnal cycle over the Amazon basin during the 2014 wet season is assessed. The WRF model coupled with a 3‐D variational data assimilation scheme reproduces the spatial variability of the precipitation diurnal cycle over the basin and the lifecycle of westward propagating MCSs initiated by the coastal sea‐breeze front. In contrast, a single morning peak in rainfall is produced by E3SM for simulations despite the nudging of large‐scale winds toward global reanalysis, indicating precipitation in E3SM is largely controlled by local convection associated with diurnal heating. The role of propagating MCS on the environment are discussed by using a multivariate perturbation analysis. We also find that the advection of moisture perturbations from ocean to inland regions have a higher correlation with the occurrence of MCSs in the Amazon than the intensity of colder air intrusion associated with sea breezes along the coast. Moreover, the presence of large cold pools over the central Amazon basin are responsible for the maintenance of propagating deep convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Global stellarator coil optimization with quadratic constraints and objectives

Most present stellarator designs are produced by costly two-stage optimization: the first for an optimized equilibrium, and the second for a coil design reproducing its magnetic configuration. Few proxies for coil complexity and forces exist at the equilibrium stage. Rapid initial state finding for both stages is a topic of active research. Most present convex coil optimization codes use the least square winding surface method by Merkel (NESCOIL), with recent improvements in conditioning, regularization, sparsity, and physics objectives. While elegant, the method is limited to modeling the norms of linear functions in coil current. We present QUADCOIL, a global coil optimization method that targets combinations of linear and quadratic functions of the current. It can directly constrain and/or minimize a wide range of physics objectives unavailable in NESCOIL and REGCOIL, including the Lorentz force, magnetic energy, curvature, field-current alignment, and the maximum density of a dipole array. QUADCOIL requires no initial guess and runs nearly $10$ 2 x faster than filament optimization. Integrating it in the equilibrium optimization stage can potentially exclude equilibria with difficult-to-design coils, without significantly increasing the computation time per iteration. QUADCOIL finds the exact, global minimum in a large parameter space when possible, and otherwise finds a well-performing approximate global minimum. It supports most regularization techniques developed for NESCOIL and REGCOIL. We demonstrate QUADCOIL’s effectiveness in coil topology control, minimizing non-convex penalties, and predicting filament coil complexity with three numerical examples.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2014

Using SpF to Achieve Petascale for Legacy Pseudospectral Applications

Pseudospectral (PS) methods possess a number of characteristics (e.g., efficiency, accuracy, natural boundary conditions) that are extremely desirable for dynamo models. Unfortunately, dynamo models based upon PS methods face a number of daunting challenges, which include exposing additional parallelism, leveraging hardware accelerators, exploiting hybrid parallelism, and improving the scalability of global memory transposes. Although these issues are a concern for most models, solutions for PS methods tend to require far more pervasive changes to underlying data and control structures. Further, improvements in performance in one model are difficult to transfer to other models, resulting in significant duplication of effort across the research community. We have developed an extensible software framework for pseudospectral methods called SpF that is intended to enable extreme scalability and optimal performance. Highlevel abstractions provided by SpF unburden applications of the responsibility of managing domain decomposition and load balance while reducing the changes in code required to adapt to new computing architectures. The key design concept in SpF is that each phase of the numerical calculation is partitioned into disjoint numerical kernels that can be performed entirely inprocessor. The granularity of domain decomposition provided by SpF is only constrained by the datalocality requirements of these kernels. SpF builds on top of optimized vendor libraries for common numerical operations such as transforms, matrix solvers, etc., but can also be configured to use open source alternatives for portability. SpF includes several alternative schemes for global data redistribution and is expected to serve as an ideal testbed for further research into optimal approaches for different network architectures. In this presentation, we will describe our experience in porting legacy pseudospectral models, MoSST and DYNAMO, to use SpF as well as present preliminary performance results provided by the improved scalability.

DYNAMO↗
DOE OSTI2021

The role of oxygen in stimulating methane production in wetlands

Methane (CH 4 ), a potent greenhouse gas, is the second most important greenhouse gas contributor to climate change after carbon dioxide (CO 2 ). The biological emissions of CH 4 from wetlands are a major uncertainty in CH 4 budgets. Microbial methanogenesis by Archaea is an anaerobic process accounting for most biological CH 4 production in nature, yet recent observations indicate that large emissions can originate from oxygenated or frequently oxygenated wetland soil layers. To determine how oxygen (O 2 ) can stimulate CH 4 emissions, we used incubations of Sphagnum peat to demonstrate that the temporary exposure of peat to O 2 can increase CH 4 yields up to 2000-fold during subsequent anoxic conditions relative to peat without O 2 exposure. Geochemical (including ion cyclotron resonance mass spectrometry, X-ray absorbance spectroscopy) and microbiome (16S rDNA amplicons, metagenomics) analyses of peat showed that higher CH 4 yields of redox-oscillated peat were due to functional shifts in the peat microbiome arising during redox oscillation that enhanced peat carbon (C) degradation. Novosphingobium species with O 2 -dependent aromatic oxygenase genes increased greatly in relative abundance during the oxygenation period in redox-oscillated peat compared to anoxic controls. Acidobacteria species were particularly important for anaerobic processing of peat C, including in the production of methanogenic substrates H 2 and CO 2 . Higher CO 2 production during the anoxic phase of redox-oscillated peat stimulated hydrogenotrophic CH 4 production by Methanobacterium species. The persistence of reduced iron (Fe(II)) during prolonged oxygenation in redox-oscillated peat may further enhance C degradation through abiotic mechanisms (e.g., Fenton reactions). The results indicate that specific functional shifts in the peat microbiome underlie O 2 enhancement of CH 4 production in acidic, Sphagnum-rich wetland soils. They also imply that understanding microbial dynamics spanning temporal and spatial redox transitions in peatlands is critical for constraining CH 4 budgets; predicting feedbacks between climate change, hydrologic variability, and wetland CH 4 emissions; and guiding wetland C management strategies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

The Cirrus Parcel Model Comparison Project

The cirrus Parcel Model Comparison Project involves the systematic comparison of current models of ice crystal nucleation and growth for specified, typical, cirrus cloud environments. In Phase 1 of the project reported here, simulated cirrus cloud microphysical properties are compared for situations of "warm" (-40 C) and "cold" (-60 C) cirrus subject to updrafts of 4, 20 and 100 centimeters per second, respectively. Five models are participating in the project. These models employ explicit microphysical schemes wherein the size distribution of each class of particles (aerosols and ice crystals) is resolved into bins. Simulations are made including both homogeneous and heterogeneous ice nucleation mechanisms. A single initial aerosol population of sulfuric acid particles is prescribed for all simulations. To isolate the treatment of the homogeneous freezing (of haze drops) nucleation process, the heterogeneous nucleation mechanism is disabled for a second parallel set of simulations. Qualitative agreement is found amongst the models for the homogeneous-nucleation-only simulations, e.g., the number density of nucleated ice crystals increases with the strength of the prescribed updraft. However, non-negligible quantitative differences are found. Systematic bias exists between results of a model based on a modified classical theory approach and models using an effective freezing temperature approach to the treatment of nucleation. Each approach is constrained by critical freezing data from laboratory studies. This information is necessary, but not sufficient, to construct consistent formulae for the two approaches. Large haze particles may deviate considerably from equilibrium size in moderate to strong updrafts (20-100 centimeters per second) at -60 C when the commonly invoked equilibrium assumption is lifted. The resulting difference in particle-size-dependent solution concentration of haze particles may significantly affect the ice nucleation rate during the initial nucleation interval. The uptake rate for water vapor excess by ice crystals is another key component regulating the total number of nucleated ice crystals. This rate, the product of ice number concentration and ice crystal diffusional growth rate, partially controls the peak nucleation rate achieved in an air parcel and the duration of the active nucleation time period.

Lin, Ruei-Fong↗
DOE OSTI2026

Plasma confinement state classification via FPP relevant microwave diagnostics

We present a parsimonious and robust machine learning approach for identifying plasma confinement states in fusion power plants (FPPs) where reliable identification of the low-confinement and high-confinement regimes is critical for safe and efficient operation. Unlike research-oriented devices, FPPs must operate with a severely constrained set of diagnostics. To address this challenge, we demonstrate that a minimalist model, using only electron cyclotron emission (ECE) signals, can achieve accurate and reliable state classification. ECE provides electron temperature profiles without the engineering or survivability issues of in-vessel probes, making it a primary candidate for FPP-relevant diagnostics. Our framework employs ECE as input, extracts features using radial basis functions, and applies a gradient boosting classifier, achieving a test accuracy of 96% (correct predictions). Robustness analysis and feature importance analyzes confirm the approach’s reliability. These results demonstrate that state-of-the-art performance is attainable from a restricted diagnostic set, paving the way for minimalist yet resilient plasma control architectures for FPPs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Optimizing LSST observing strategy for weak lensing systematics

ABSTRACT The Legacy Survey of Space and Time (LSST) survey will provide unprecedented statistical power for measurements of dark energy. Consequently, controlling systematic uncertainties is becoming more important than ever. The LSST observing strategy will affect the statistical uncertainty and systematics control for many science cases; here, we focus on weak lensing (WL) systematics. The fact that the LSST observing strategy involves hundreds of visits to the same sky area provides new opportunities for systematics mitigation. We explore these opportunities by testing how different dithering strategies (pointing offsets and rotational angle of the camera in different exposures) affect additive WL shear systematics on a baseline operational simulation, using the ρ-statistics formalism. Some dithering strategies improve systematics control at the end of the survey by a factor of up to ∼3–4 better than others. We find that a random translational dithering strategy, applied with random rotational dithering at every filter change, is the most effective of those strategies tested in this work at averaging down systematics. Adopting this dithering algorithm, we explore the effect of varying the area of the survey footprint, exposure time, number of exposures in a visit, and exposure to the Galactic plane. We find that any change that increases the average number of exposures (in filters relevant to WL) reduces the additive shear systematics. Some ways to achieve this increase may not be favorable for the WL statistical constraining power or for other probes, and we explore the relative trade-offs between these options given constraints on the overall survey parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1988

The expanded Lagrangian system for constrained optimization problems

Smooth penalty functions can be combined with numerical continuation/bifurcation techniques to produce a class of robust and fast algorithms for constrained optimization problems. The key to the development of these algorithms is the Expanded Lagrangian System which is derived and analyzed in this work. This parameterized system of nonlinear equations contains the penalty path as a solution, provides a smooth homotopy into the first-order necessary conditions, and yields a global optimization technique. Furthermore, the inevitable ill-conditioning present in a sequential optimization algorithm is removed for three penalty methods: the quadratic penalty function for equality constraints, and the logarithmic barrier function (an interior method) and the quadratic loss function (an interior method) for inequality constraints. Although these techniques apply to optimization in general and to linear and nonlinear programming, calculus of variations, optimal control and parameter identification in particular, the development is primarily within the context of nonlinear programming.

Poore, A. B.↗
NASA NTRS2007

Aeroelastic Model Structure Computation for Envelope Expansion

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion that may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of non-linear aeroelastic systems. The LASSO minimises the residual sum of squares with the addition of an l(Sub 1) penalty term on the parameter vector of the traditional l(sub 2) minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudo-linear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Active Aeroelastic Wing project using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

Kukreja, Sunil L.↗