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At least 1,639 records · Page 91

Two systems analyses of SETI

The problem of receiving and identifying a single microwave signal transmitted by extraterrestrial intelligent beings is analyzed in the cases where the signal is designed to catch our attention and the signal is designed for internal purposes of another civilization. Six variables which yield uncertainty as to the exact signal which should be searched for are described: polarization, modulation, flux level, direction, frequency (including bandwidth and drift rate), and time. It is shown that if all reasonable variations of these parameters are to be examined sequentially for 1000 seconds, the search would take over a million times longer than the age of the Universe. Ways to simplify the search are considered, including widening the frequency bin, selecting specific targets, cutting the observation time, using a Fourier transform device for data processing, and building larger antennas as well as better low-noise receivers.

Machol, R. E.↗

Development of Prototype Micro-Lidar using Narrow Linewidth Semiconductor Lasers for Mars Boundary Layer Wind and Dust Opacity Profiles

We have developed a compact Doppler lidar concept which utilizes recent developments in semiconductor diode laser technology in order to be considered suitable for wind and dust opacity profiling in the Mars lower atmosphere from a surface location. The current understanding of the Mars global climate and meteorology is very limited, with only sparse, near-surface data available from the Viking and Mars Pathfinder landers, supplemented by long-range remote sensing of the Martian atmosphere. The in situ measurements from a lander-based Doppler lidar would provide a unique dataset particularly for the boundary layer. The coupling of the radiative properties of the lower atmosphere with the dynamics involves the radiative absorption and scattering effects of the wind-driven dust. Variability in solar irradiance, on diurnal and seasonal time scales, drives vertical mixing and PBL (planetary boundary layer) thickness. The lidar data will also contribute to an understanding of the impact of wind-driven dust on lander and rover operations and lifetime through an improvement in our understanding of Mars climatology. In this paper we discuss the Mars lidar concept, and the development of a laboratory prototype for performance studies, using, local boundary layer and topographic target measurements.

Menzies, Robert T.↗

Ground Reaction Forces During Locomotion in Simulated Microgravity

Significant losses in bone density and mineral, primarily in the lower extremities have been reported following exposure to weightlessness. Recent investigations suggest that mechanical influences such as bone deformation and strain rate may be critically important in stimulating new bone formation. It was hypothesized that velocity, cadence and harness design would significantly affect lower limb impact forces during treadmill exercise in simulated zero gravity (0G). A ground-based hypogravity simulator was used to investigate which factors affect limb loading during tethered treadmill exercise. A fractional factorial design was used and 12 subjects were studied. The results showed that running on active and passive treadmills in the simulator with a tethering force close to the maximum comfortable level produced similar magnitudes for the peak ground reaction force. It was also found that these maximum forces were significantly lower than those obtained during overground trials, even when the speeds of locomotion in the simulator were 66 % greater than those in 1 G. Cadence had no effect on any of the response variables. The maximum rate of force application (DFDT-Max) was similar for overground running and exercise in simulated 0G, provided that the "weightless subjects ran on a motorized treadmill. These findings have implications for the use of treadmill exercise as a countermeasure for hypokinetic osteoporosis. As the relationship between mechanical factors and osteogenesis becomes better understood, results from human experiments in 0G simulators will help to design in-flight exercise programs that are more closely targeted to generate appropriate mechanical stimuli.

Davis, B. L.↗

"Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed Autonomy Traffic"

This paper introduces a novel control framework for Lagrangian variable speed limits in hybrid traffic flow environments utilizing automated vehicles (AVs). The framework was validated using a fleet of 100 connected automated vehicles as part of the largest coordinated open-road test designed to smooth traffic flow. The framework includes two main components: a high-level controller deployed on the server side, named Speed Planner, and low-level controllers called vehicle controllers deployed on the vehicle side. The Speed Planner designs and updates target speeds for the vehicle controllers based on real-time Traffic State Estimation (TSE) [1]. The Speed Planner comprises two modules: a TSE enhancement module and a target speed design module. The TSE enhancement module is designed to minimize the effects of inherent latency in the received traffic information and to improve the spatial and temporal resolution of the input traffic data. The target speed design module generates target speed profiles with the goal of improving traffic flow. The vehicle controllers are designed to track the target speed meanwhile responding to the surrounding situation. The numerical simulation indicates the performance of the proposed method: the bottleneck throughput has increased by 5.01%, and the speed standard deviation has been reduced by a significant 34.36%. We further showcase an operational study with a description of how the controller was implemented on a field-test with 100 AVs and its comprehensive effects on the traffic flow.

Wang, Han↗

Multiscale influenza forecasting

Abstract Influenza forecasting in the United States (US) is complex and challenging due to spatial and temporal variability, nested geographic scales of interest, and heterogeneous surveillance participation. Here we present Dante, a multiscale influenza forecasting model that learns rather than prescribes spatial, temporal, and surveillance data structure and generates coherent forecasts across state, regional, and national scales. We retrospectively compare Dante’s short-term and seasonal forecasts for previous flu seasons to the Dynamic Bayesian Model (DBM), a leading competitor. Dante outperformed DBM for nearly all spatial units, flu seasons, geographic scales, and forecasting targets. Dante’s sharper and more accurate forecasts also suggest greater public health utility. Dante placed 1st in the Centers for Disease Control and Prevention’s prospective 2018/19 FluSight challenge in both the national and regional competition and the state competition. The methodology underpinning Dante can be used in other seasonal disease forecasting contexts having nested geographic scales of interest.

59 BASIC BIOLOGICAL SCIENCES↗

HELIOSEISMOLOGY OF PRE-EMERGING ACTIVE REGIONS. I. OVERVIEW, DATA, AND TARGET SELECTION CRITERIA

This first paper in a series describes the design of a study testing whether pre-appearance signatures of solar magnetic active regions were detectable using various tools of local helioseismology. The ultimate goal is to understand flux-emergence mechanisms by setting observational constraints on pre-appearance subsurface changes, for comparison with results from simulation efforts. This first paper provides details of the data selection and preparation of the samples, each containing over 100 members, of two populations: regions on the Sun that produced a numbered NOAA active region, and a 'control' sample of areas that did not. The seismology is performed on data from the GONG network; accompanying magnetic data from SOHO/MDI are used for co-temporal analysis of the surface magnetic field. Samples are drawn from 2001-2007, and each target is analyzed for 27.7 hr prior to an objectively determined time of emergence. The results of two analysis approaches are published separately: one based on averages of the seismology- and magnetic-derived signals over the samples, another based on Discriminant Analysis of these signals, for a statistical test of detectable differences between the two populations. We include here descriptions of a new potential-field calculation approach and the algorithm for matching sample distributions over multiple variables. We describe known sources of bias and the approaches used to mitigate them. We also describe unexpected bias sources uncovered during the course of the study and include a discussion of refinements that should be included in future work on this topic.

79 ASTRONOMY AND ASTROPHYSICS↗

Not even 6 dB: Gaussian quantum illumination in thermal background

Abstract In analyses of target detection with Gaussian state transmitters in a thermal background, the thermal occupation is taken to depend on the target reflectivity in a way which simplifies the analysis of the symmetric quantum hypothesis testing problem. However, this assumption precludes comparison of target detection performance between an arbitrary transmitter and a vacuum state transmitter, i.e. ‘detection without illumination’, which is relevant in a bright thermal background because a target can be detected by its optical shadow or some other perturbation of the background. Using a target-agnostic thermal environment leads to the result that the oft-claimed 6 dB possible reduction in the quantum Chernoff exponent for a two-mode squeezed vacuum transmitter over a coherent state transmitter in high-occupation thermal background is an unachievable limiting value, only occurring in a limit in which the target detection problem is ill-posed. Further analyzing quantum illumination in a target-agnostic thermal environment shows that a weak single-mode squeezed transmitter performs worse than ‘no illumination’, which is explained by the noise-increasing property of reflected low-intensity squeezed light.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SU-E-T-761: TOMOMC, A Monte Carlo-Based Planning VerificationTool for Helical Tomotherapy

Purpose: Present a new Monte Carlo code (TOMOMC) to calculate 3D dose distributions for patients undergoing helical tomotherapy treatments. TOMOMC performs CT-based dose calculations using the actual dynamic variables of the machine (couch motion, gantry rotation, and MLC sequences). Methods: TOMOMC is based on the GEPTS (Gama Electron and Positron Transport System) general-purpose Monte Carlo system (Chibani and Li, Med. Phys. 29, 2002, 835). First, beam models for the Hi-Art Tomotherpy machine were developed for the different beam widths (1, 2.5 and 5 cm). The beam model accounts for the exact geometry and composition of the different components of the linac head (target, primary collimator, jaws and MLCs). The beams models were benchmarked by comparing calculated Pdds and lateral/transversal dose profiles with ionization chamber measurements in water. See figures 1–3. The MLC model was tuned in such a way that tongue and groove effect, inter-leaf and intra-leaf transmission are modeled correctly. See figure 4. Results: By simulating the exact patient anatomy and the actual treatment delivery conditions (couch motion, gantry rotation and MLC sinogram), TOMOMC is able to calculate the 3D patient dose distribution which is in principal more accurate than the one from the treatment planning system (TPS) since it relies on the Monte Carlo method (gold standard). Dose volume parameters based on the Monte Carlo dose distribution can also be compared to those produced by the TPS. Attached figures show isodose lines for a H&N patient calculated by TOMOMC (transverse and sagittal views). Analysis of differences between TOMOMC and TPS is an ongoing work for different anatomic sites. Conclusion: A new Monte Carlo code (TOMOMC) was developed for Tomotherapy patient-specific QA. The next step in this project is implementing GPU computing to speed up Monte Carlo simulation and make Monte Carlo-based treatment verification a practical solution.

60 APPLIED LIFE SCIENCES↗

A multi-specific, multi-affinity antibody platform neutralizes sarbecoviruses and confers protection against SARS-CoV-2 in vivo

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has been responsible for a global pandemic. Monoclonal antibodies (mAbs) have been used as antiviral therapeutics; however, these therapeutics have been limited in efficacy by viral sequence variability in emerging variants of concern (VOCs) and in deployment by the need for high doses. In this study, we leveraged the multi-specific, multi-affinity antibody (Multabody, MB) platform, derived from the human apoferritin protomer, to enable the multimerization of antibody fragments. MBs were shown to be highly potent, neutralizing SARS-CoV-2 at lower concentrations than their corresponding mAb counterparts. In mice infected with SARS-CoV-2, a tri-specific MB targeting three regions within the SARS-CoV-2 receptor binding domain was protective at a 30-fold lower dose than a cocktail of the corresponding mAbs. Furthermore, we showed in vitro that mono-specific MBs potently neutralize SARS-CoV-2 VOCs by leveraging augmented avidity, even when corresponding mAbs lose their ability to neutralize potently, and that tri-specific MBs expanded the neutralization breadth beyond SARS-CoV-2 to other sarbecoviruses. Our work demonstrates how avidity and multi-specificity combined can be leveraged to confer protection and resilience against viral diversity that exceeds that of traditional monoclonal antibody therapies.

60 APPLIED LIFE SCIENCES↗

Estimating the Value of Utility-Scale Solar Technologies in California Under a 40% Renewable Portfolio Standard

Concentrating solar power with thermal energy storage (CSP-TES) is a unique source of solar energy in that its output can be shifted over time. The ability of CSP-TES to be a flexible source of generation may be particularly valuable in regions with high overall penetration of solar energy, such as the state of California. California's Renewable Portfolio Standard (RPS) requires the state to increase generation from eligible renewable energy resources to reach 33% of retail electricity sales by 2020. Beyond 2020, California targets a further reduction in greenhouse gas emissions. To help reach this goal, current California governor Jerry Brown has stated that a higher 40% RPS might be reachable in the near term. The levelized cost of energy is generally emphasized when assessing the economic viability of renewable energy systems implemented to achieve the RPS. However, the operational and capacity benefits of such systems are often ignored, which can lead to incorrect economic comparisons between CSP-TES and variable renewable generation technologies such as solar photovoltaics (PV). Here we evaluate a 40% RPS scenario in a California grid model with PV or CSP-TES providing the last 1% of RPS energy. We compare the technical and economic implications of integrating either solar technology under several sensitivities, finding that the ability to displace new conventional thermal generation capacity may be the largest source of value of CSP-TES compared to PV at high solar penetrations.

14 SOLAR ENERGY↗

Air-breathing hypersonic vehicle guidance and control studies: An integrated trajectory/control analysis methodology, phase 2

An integrated trajectory/control analysis algorithm has been used to generate trajectories and desired control strategies for two different hypersonic air-breathing vehicle models and orbit targets. Both models used cubic spline curve fit tabulated winged-cone accelerator vehicle representations. Near-fuel-optimal, horizontal takeoff trajectories, imposing a dynamic pressure limit of 1000 psf, were developed. The first model analysis case involved a polar orbit and included the dynamic effects of using elevons to maintain longitudinal trim. Analysis results indicated problems with the adequacy of the propulsion model and highlighted dynamic pressure/altitude instabilities when using vehicle angle of attack as a control variable. Also, the magnitude of computed elevon deflections to maintain trim suggested a need for alternative pitch moment management strategies. The second analysis case was reformulated to use vehicle pitch attitude relative to the local vertical as the control variable. A new, more realistic, air-breathing propulsion model was incorporated. Pitch trim calculations were dropped and an equatorial orbit was specified. Changes in flight characteristics due to the new propulsion model have been identified. Flight regimes demanding rapid attitude changes have been noted. Also, some issues that would affect design of closed-loop controllers were ascertained.

Hattis, Philip D.↗

Geoscience Laser Altimeter System: Characteristics and Performance of the Altimeter Receiver

The Geoscience Laser Altimeter System (GLAS) on board ICESat spacecraft measures the surface height (altimetry) via the time of flight of its 1064 nm laser pulse. The GLAS laser transmitter produces 6 ns wide pulses with 70 mJ energy at 1064 nm at a 40 Hz rate. The altimeter receiver consists of a telescope, aft optics, a silicon avalanche photodiode, and electronic amplifiers. The transmitted and echo pulse waveforms are digitized at 1 GHz rate. The laser pulse time of flight is determined on the ground from the two digitized pulse waveforms and their positions in the full waveform record (about 5.4 ms ong) by computing the pulse centroids or by curve fitting. The GLAS receiver algorithms in on board software selects the two waveform segments containing the transmitted and the echo pulses and sends them to ground. The probability of echo pulse detection and the accuracy of time of flight measurement depend on the received signal level, the background light within the receiver field of view, the inherent detector and amplifier noise, the quantization of the digitizer, and some times by cloud obscurations. A receiver model has been developed to calculate the probability of detection and accuracy of the altimeter measurements with these noise sources. From prelaunch testing, the minimum detectable echo pulse energy for 90% detection probability was about 0.1 fj/pulse onto the detector. Such a receiver sensitivity allows GLAS to measure the surface height through clouds with optical density less than 2. The echo pulse energy required to achieve 10 cm ranging accuracy was found to be about 3 times higher than the minimum detectable signal level. The smallest single shot range measurement error, which was determined by ranging to a fixed target with strong echo pulses and no background light, was 2 to 3cm. The maximum linear response echo pulse energy was 10 fJ/pulse for the strongest echo signals, assuming a Lambertian scattering snow surface, clear sky atmosphere transmission, and no pulse width spreading due to surface slopes. Results from the initial 38 days of GLAS operation on-orbit with Laser 1, showed the echo pulse energies varied, as expected, over a wide dynamic range due to the variability of atmosphere transmission and Earth surface characteristics. The receiver was able to reliably detect the ground surface echoes and measure time of flight under such dynamic conditions, except when there were dense clouds. When over Antarctica, the echo pulse energies were several times stronger than predicted. This suggests that the 1064 nm backscattering from the snow pack and ice-sheet &ce are not completely Lambertian but is somewhat peaked at opposit.ion. With Laser 1, the peak amplitude of the echo pulses from flat ice sheets under clear sky conditions exceeded the linear response range of the receiver, causing some pulse waveform distortion due to saturation. We have characterized the effects of receiver saturation on the time of flight, pulse width, and pulse energy measurements for flat surface by testing a night spare detector in the lab with simulated echo pulses. A data processing algorithm that minimizes the errors due to saturation for these measurements are described.

Sun, Xiao-Li↗

Human Performance of Novice Schedulers for Complex Spaceflight Operations Timelines

Objective: Investigate the effects on human performance as a function of scheduling task complexity for novice schedulers creating spaceflight timelines. Background: Future astronauts will be expected to self-schedule, yet will not be experts in creating timelines that meet complex constraints inherent to spaceflight operations. Method: Conducted a within-subject experiment to measure scheduling efficiency, effectiveness, workload and situation awareness while varying scheduling task complexity factors, namely number of constraints and types of constraints. Results: Fifteen participants completed various scheduling problems. Performance differences were identified between the independent variables. There was a main effect due to the number of constraints and type of constraint for efficiency, effectiveness, and workload. Significant interactions were observed in situation awareness and workload for certain types of constraints. Results also suggest that a lower number of constraints may be manageable by novice schedulers when compared to scheduling activities without constraints. Conclusion: Results suggest that novice schedulers performance decreases with high number of constraints and future scheduling aids may have to be targeted to type of constraint. Application: Knowledge on the effect of scheduling task complexity will help design scheduling systems that will enable self-scheduling for future astronauts. It will also inform other domains that conduct complex scheduling, such as nursing and manufacturing.

scheduling↗

Estimating the Value of Utility-Scale Solar Technologies in California Under a 40% Renewable Portfolio Standard (Report Summary) (Presentation)

Concentrating solar power with thermal energy storage (CSP-TES) is a unique source of solar energy in that its output can be shifted over time. The ability of CSP-TES to be a flexible source of generation may be particularly valuable in regions with high overall penetration of solar energy, such as the state of California. California's Renewable Portfolio Standard (RPS) requires the state to increase generation from eligible renewable energy resources to reach 33% of retail electricity sales by 2020. Beyond 2020, California targets a further reduction in greenhouse gas emissions. To help reach this goal, current California governor Jerry Brown has stated that a higher 40% RPS might be reachable in the near term. The levelized cost of energy is generally emphasized when assessing the economic viability of renewable energy systems implemented to achieve the RPS. However, the operational and capacity benefits of such systems are often ignored, which can lead to incorrect economic comparisons between CSP-TES and variable renewable generation technologies such as solar photovoltaics (PV). Here we evaluate a 40% RPS scenario in a California grid model with PV or CSP-TES providing the last 1% of RPS energy. We compare the technical and economic implications of integrating either solar technology under several sensitivities, finding that the ability to displace new conventional thermal generation capacity may be the largest source of value of CSP-TES compared to PV at high solar penetrations.

14 SOLAR ENERGY↗

Verification, Validation, and Calibration Through a Causal Lens

While typical validation and verification approaches focus on identifying the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on identifying causal relationships between data elements. Statistical and machine-learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between data sets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify, and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles, it is known as a directed acyclic graph. A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts can identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗

A Robust Data-Driven Approach for Mechanical Serial Sectioning

Mechanical serial sectioning (MSS) provides detailed microstructural information across large length scales. By repeatedly removing thin layers of material and imaging the exposed surface, a 3D representation of a specimen’s internal structure can be constructed, enabling failure analysis and feature identification that are otherwise inaccessible via conventional 2D or nondestructive evaluation techniques. Achieving consistent and accurate material removal can be challenging due to system variability, requiring an experienced operator to manually adjust parameters, prolonging data collection times and necessitating post-processing routines to standardize the data. Here, to address these challenges, this paper presents the employment of a one-step model predictive control (MPC) framework tailored to a run-to-run (R2R) controller. The R2R-MPC controller automates the parameter selection process, improving the consistency of material removal through iterative feedback for disturbance rejection and accurate tracking of the target removal rate. Using a data-driven approach, the controller robustly adapts to changing material characteristics. The effectiveness of the R2R-MPC controller is demonstrated through simulation and experimental results and compared to previous data collection procedures.

3D Materials Science↗

Thermal energy evolution and mechanical deformation of monocrystalline yttria-stabilized zirconia nanoparticles in aerosol deposition processes

Aerosol deposition (AD) is a coating process wherein aerosol particles are impacted on a target substrate. There are fundamental differences between the AD process (cold impact), where particle translational kinetic energy is high and thermal energy is low, and thermal spray deposition (thermal impact), where translational energy is lower but thermal energy is high. To better compare cold and thermal impact effects on particles, we carried out molecular dynamics simulations using yttria-stabilized zirconia (YSZ) nanoparticles on YSZ substrates as a model system. We performed cold impact simulations at 300 K with variable impact velocity in the 500 ms –1 –1500 ms –1 range to understand how increasing translational kinetic energy affects thermal energy and mechanical evolution. We then performed thermal impact simulations at variable temperature and impact velocity, but where the total kinetic energy of the nanoparticle was equivalent to that of a 300 K, 1000 impact. In cold impact, the temperature increases in YSZ nanoparticles at a rate of 10 13 – 10 14 K s –1 , and large temperature gradients result. Conversely, in thermal impact, nanoparticle temperatures remain uniform. Furthermore, the temperature gradients during cold impact coincide with plastic deformation in nanoparticles, while with larger thermal energies, plastic deformation is reduced.

42 ENGINEERING↗

What are the low- Q and large- x boundaries of collinear QCD factorization theorems?

Familiar factorized descriptions of classic QCD processes such as deeply-inelastic scattering (DIS) apply in the limit of very large hard scales, much larger than nonperturbative mass scales and other nonperturbative physical properties like intrinsic transverse momentum. Since many interesting DIS studies occur at kinematic regions where the hard scale, $Q \sim$ 1-2 GeV, is not very much greater than the hadron masses involved, and the Bjorken scaling variable $x_{bj}$ is large, $x_{bj} \gtrsim 0.5$, it is important to examine the boundaries of the most basic factorization assumptions and assess whether improved starting points are needed. Using an idealized field-theoretic model that contains most of the essential elements that a factorization derivation must confront, we retrace in this paper the steps of factorization approximations and compare with calculations that keep all kinematics exact. We examine the relative importance of such quantities as the target mass, light quark masses, and intrinsic parton transverse momentum, and argue that a careful accounting of parton virtuality is essential for treating power corrections to collinear factorization. Finally, we use our observations to motivate searches for new or enhanced factorization theorems specifically designed to deal with moderately low-$Q$ and large-$x_{bj}$ physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗