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NASA NTRS2020

A Generalized Guidance Approach to In-Space Solid-Propellant Vehicle Maneuvers

Exploration-class vehicles that require fully autonomous ascent and descent must employ robust, explicit path-adaptive guidance algorithms that can operate in a wide range of physical environments. Vehicle designs that employ solid-propellant rocket motors (SRMs) for maneuvers are attractive from a system engineering perspective because of their simplicity and reliability but may cause complications for both mission designers and GNC engineers when dealing with total impulse uncertainty, as well as proper energy management of a motor with an uncontrolled cutoff time. This paper presents a simplified guidance algorithm, named Simple Cross-Product Steering (SxS), that was derived during early studies of NASA’s Mars Sample Return mission’s Mars Ascent Vehicle. The algorithm takes roots in a flight-proven guidance algorithm commonly referred to as Cross-Product Steering. This algorithm has been shown to provide sufficient guidance accuracy for in-space SRM burns in a simulated Martian environment, and preliminary studies have been conducted to test the algorithm in a solid-propellant lunar braking scenario. A method for predicting proper motor ignition time during execution of the Cross-Product Steering algorithm is the primary contribution of this paper. Mechanization notes are also provided that were realized in early phases of MAV. Results are shown for an example ascent vehicle a simulated Mars environment.

Jason M Everett↗

NASA NTRS1988

Constitutive and life modeling of single crystal blade alloys for root attachment analysis

Work to develop fatigue life prediction and constitutive models for uncoated attachment regions of single crystal gas turbine blades is described. At temperatures relevant to attachment regions, deformation is dominated by slip on crystallographic planes. However, fatigue crack initiation and early crack growth are not always observed to be crystallographic. The influence of natural occurring microporosity will be investigated by testing both hot isostatically pressed and conventionally cast PWA 1480 single crystal specimens. Several differnt specimen configurations and orientations relative to the natural crystal axes are being tested to investigate the influence of notch acuity and the material's anisotropy. Global and slip system stresses in the notched regions were determined from three dimensional stress analyses and will be used to develop fatigue life prediction models consistent with the observed lives and crack characteristics.

Meyer, T. G.↗

NASA NTRS1994

Data driven propulsion system weight prediction model

The objective of the research was to develop a method to predict the weight of paper engines, i.e., engines that are in the early stages of development. The impetus for the project was the Single Stage To Orbit (SSTO) project, where engineers need to evaluate alternative engine designs. Since the SSTO is a performance driven project the performance models for alternative designs were well understood. The next tradeoff is weight. Since it is known that engine weight varies with thrust levels, a model is required that would allow discrimination between engines that produce the same thrust. Above all, the model had to be rooted in data with assumptions that could be justified based on the data. The general approach was to collect data on as many existing engines as possible and build a statistical model of the engines weight as a function of various component performance parameters. This was considered a reasonable level to begin the project because the data would be readily available, and it would be at the level of most paper engines, prior to detailed component design.

Gerth, Richard J.↗

DOE OSTI2024

Pan-tropical daily L-band microwave land surface emissivity retrieval from GNSS-R observations

The uncertainties in microwave land surface emissivity (MLSE) measurements have long limited the use of spaceborne microwave radiometer data. As an emerging observation method, Global Navigation Satellite System Reflectometry (GNSS-R) has demonstrated great potential in several land and ocean applications. In this study, a method for obtaining daily MLSE dataset in the pan-tropical region from Cyclone GNSS (CYGNSS) observations is presented and evaluated. The CYGNSS observations are first aggregated into the Equal-Area-Scalable-Earth (EASE) 2.0 36 km grid by a combined weight function of distance, time, and signal-to-noise ratio variance. Then, the method employs a pixel-by-pixel regression algorithm to conduct the daily MLSE retrieval using reference emissivity derived from the Soil Moisture Active Passive (SMAP) brightness temperature. The CYGNSS MLSE shows good agreement with SMAP MLSE, delivering an overall root-mean-square error (RMSE) of 0.022 and 0.017 for horizontal and vertical polarization, respectively, during the training set spanning the whole year of 2018. Furthermore, on the test set from January 2019 to May 2019, the RMSE values amounted to 0.030 and 0.023 for horizontal and vertical polarization, respectively. Temperature records from the International Soil Moisture Network are employed to calculate the emissivity and for in-situ validation, which yield an RMSE of 0.034 and 0.026 for the two polarizations, respectively. The proposed algorithm provides an encouraging approach to obtain accurate daily MLSE dataset for microwave remote sensing. Compared to the SMAP MLSE, the CYGNSS MLSE has a remarkable improvement of 86% in temporal resolution, greatly complementing the existing microwave emissivity datasets.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Real-Time Automated pH Control within Batch Processes Relying on Raman pH Measurement

Nuclear fission is an energy source that can provide consistent power with very low associated carbon emissions. However, management of the used nuclear fuel is an important aspect of the application of nuclear power. Recycling of useful components from used fuel is an attractive option, but this involves chemical processing of the fuel. Possible chemical separation technologies that might be used in this regard are sensitive to solution pH. Raman spectroscopy is a promising technique for monitoring the pH of solutions in real time. Classical pH probes are too fragile to be used in the harsh environments encountered in nuclear fuel processing. Raman probes are robust and can withstand these harsh environments to track pH. Coupled with chemometric analysis, the demonstration of the use of Raman spectroscopy to track and predict the pH in carboxylate-buffered systems is made possible. Utilizing this spectroscopy in conjunction with Programmable Logic Controllers mimics industrial control systems used in many modern industrial settings. This showcases a pragmatic approach toward leveraging Raman spectroscopy and chemometric model outputs as inputs for a real-time control system. The model to predict pH created by chemometrics proved to be successful in tracking pH. The optimal pH for TALSPEAK extraction of lanthanides and actinides from aqueous solution is known to proceed in a narrow pH range of around pH = 2.8 ± 0.1. This study uses Raman optical monitoring and automated control to return and maintain solution pH within this range after acid or base perturbations move the solution pH well outside this region. Root-mean-square errors show that pH changes measured using Raman spectroscopy on the batch process solution are reliably measured and used to automatically correct and maintain solution pH. Measurement of solution pH tracks favorably with electrochemical pH probe comparison measurements. As a result, the ability to showcase Raman spectroscopy paired with chemometrics analysis acts as a durable, better alternative data source compared to traditional pH probes to optimize the separation efficiency in the used nuclear fuel processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Curving the space by non-Hermiticity

Quantum systems are often classified into Hermitian and non-Hermitian ones. Extraordinary non-Hermitian phenomena, ranging from the non-Hermitian skin effect to the supersensitivity to boundary conditions, have been widely explored. Whereas these intriguing phenomena have been considered peculiar to non-Hermitian systems, we show that they can be naturally explained by a duality between non-Hermitian models in flat spaces and their counterparts, which could be Hermitian, in curved spaces. For instance, prototypical one-dimensional (1D) chains with uniform chiral tunnelings are equivalent to their duals in two-dimensional (2D) hyperbolic spaces with or without magnetic fields, and non-uniform tunnelings could further tailor local curvatures. Such a duality unfolds deep geometric roots of non-Hermitian phenomena, delivers an unprecedented routine connecting Hermitian and non-Hermitian physics, and gives rise to a theoretical perspective reformulating our understandings of curvatures and distance. In practice, it provides experimentalists with a powerful two-fold application, using non-Hermiticity to engineer curvatures or implementing synthetic curved spaces to explore non-Hermitian quantum physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Building fault detection data to aid diagnostic algorithm creation and performance testing

It is estimated that approximately 4-5% of national energy consumption can be saved through corrections to existing commercial building controls infrastructure and resulting improvements to efficiency. Correspondingly, automated fault detection and diagnostics (FDD) algorithms are designed to identify the presence of operational faults and their root causes. A diversity of techniques is used for FDD spanning physical models, black box, and rule-based approaches. A persistent challenge has been the lack of common datasets and test methods to benchmark their performance accuracy. This article presents a first of its kind public dataset with ground-truth data on the presence and absence of building faults. This dataset spans a range of seasons and operational conditions and encompasses multiple building system types. It contains information on fault severity, as well as data points reflective of the measurements in building control systems that FDD algorithms typically have access to. The data were created using simulation models as well as experimental test facilities, and will be expanded over time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

An ML-based terrestrial data fusion and augmentation framework to enable advanced understanding of the terrestrial carbon and water interactions

Soil moisture is essential to the terrestrial carbon and water cycles and land–atmosphere interactions. There are various types of soil moisture data, and each type has the distinct spatiotemporal strengths and limitations, depending on the diverse applications and retrieval methodologies of different data types (Li et al., in review; The PNNL-82151 FY23 Report). However, the limitations of different soil moisture data in terms of accuracy and spatiotemporal coverage hinder our ability to further understand the soil moisture dynamics across scales. To have a gap free soil moisture data product with a fine spatiotemporal coverage and vertical profiles, we train extreme gradient boosting (XGBoost) models by using (1) in-situ soil moisture measurements from the International Soil Moisture Network (ISMN), (2) soil moisture from the ECMWF reanalysis (ERA) at the 9 km and sub-daily spatiotemporal resolution, (3) the Daymet meteorological fields, and (4) data products that characterize surface conditions, including soil texture, organic content, topography, vegetation type, and rooting depth. We use the trained XGBoost models that have consistent performance across seven soil layers, i.e., 0–5 cm, 5–10 cm, 10–20 cm, 20–40 cm, 40–60 cm, 60–100 cm, and 100–200 cm, and the gridded model predictors to generate a soil moisture data at the 1 km and daily spatiotemporal resolution for the Continental United States (CONUS) from 2001–2020. This dataset can be broadly used for Earth system model benchmark, monitoring extreme weathers, making informed decisions regarding agriculture, water resource management, climate change mitigation, and ecosystem preservation.

58 GEOSCIENCES↗

NASA NTRS1992

Advanced Technology Blade testing on the XV-15 Tilt Rotor Research Aircraft

The XV-15 Tilt Rotor Research Aircraft has just completed the first series of flight tests with the Advanced Technology Blade (ATB) rotor system. The ATB are designed specifically for flight research and provide the ability to alter blade sweep and tip shape. A number of problems were encountered from first installation through envelope expansion to airplane mode flight that required innovative solutions to establish a suitable flight envelope. Prior to operation, the blade retention hardware had to be requalified to a higher rated centrifugal load, because the blade weight was higher than expected. Early flights in the helicopter mode revealed unacceptably high vibratory control system loads which required a temporary modification of the rotor controls to achieve higher speed flight and conversion to airplane mode. The airspeed in airplane mode was limited, however, because of large static control loads. Furthermore, analyses based on refined ATB blade mass and inertia properties indicated a previously unknown high-speed blade mode instability, also requiring airplane-mode maximum airspeed to be restricted. Most recently, a structural failure of an ATB cuff (root fairing) assembly retention structure required a redesign of the assembly. All problems have been addressed and satisfactory solutions have been found to allow continued productive flight research of the emerging tilt rotor concept.

Wellman, Brent↗

DOE OSTI2024

Getting to the root of the problem: Soil carbon and microbial responses to root inputs within a buried paleosol along an eroding hillslope in southwestern Nebraska, USA

Large quantities of soil carbon (C) can persist within paleosols for millennia due to burial and subsequent isolation from plant-derived inputs, atmospheric conditions, and microbial activity at the modern surface. Erosion exposes buried soils to modern root-derived C influx via root exudation and root turnover, thus stimulating microbial activity leading to SOC decomposition and accumulation through organo-mineral stabilization of modern C. With this study we aim to quantify how modern root-derived C inputs impact paleosol C decomposition and stabilization across varying degrees of isolation from modern surface conditions in southwestern Nebraska, USA, where hillslope erosion is bringing a buried Late-Pleistocene-early Holocene paleosol (the “Brady Soil”) closer to the modern surface. We collected Brady Soil samples from 0.2m, 0.4m, and 1.2m below the modern surface and conducted two lab-based incubations. Soils were amended with either (1) a lab-synthesized mixture of low molecular weight compounds (12 atom% 13 C), or (2) 13 C enriched root residues (92 atom% 13 C), in 30-day and 240-day incubation experiments, respectively. Here we determined microbial responses to synthetic root exudates and residues by partitioning the 13 C label from Brady Soil C, including measurements of total, root, and primed C respiration, microbial biomass C (MBC), microbial C use efficiency (CUE). To assess the capacity of isolated paleosols to accrue modern plant C, we used Nano-scale Secondary Ion Mass Spectrometry imaging. We found that: (1) adding root-derived C inputs primed Brady Soil C across all depths, and was mediated by depth and composition of root additions; (2) root-derived C inputs stimulated microbial biomass C (MBC) growth similarly across depths, but the magnitude of CUE and MBC varied by chemistry of root-derived additions; (3) new particulate organic matter was incorporated into mineral-associated pools over time; (4) material from the added root residues was found in association with bacterial cells and fungal hyphae as well as with soil aggregate and mineral surfaces. Our study shows that paleosols defy expectations of C content and reactivity with depth, and changes in land cover and climate will expose buried paleosols to modern surface conditions, increasing respired C. This work highlights the importance of evaluating the role resurfacing buried soils through landscape change plays in C cycle feedbacks to the climate system.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1976

Surface photometry of Virgo cluster galaxies - Barred galaxies

Photographic surface photometry in B and V is presented for three barred galaxies in the Virgo cluster: N4548, N4596, and N4608. Intercomparisons of luminosity and color profiles and standard photometric parameters indicate that for these galaxies: (1) the nuclear component follows the fourth-root-of-radius luminosity law for both B and V, (2) the luminosity profiles along the bar show a characteristic shoulder with a slight fall in B-V color profile at the brightest point in the bar, the strength of the effect declining from N4548 to N4608, (3) the integrated bar component is slightly bluer than the nucleus, and (4) as the disk, arm, and ring components contribute less to the total luminosity of the system, the contribution of the bar increases as does the equivalent gradient.

Benedict, G. F.↗

NASA NTRS2006

Adaptive Changes In Postural Equilibrium And Motion Sickness Following Repeated Exposures To Virtual Environments

Virtual environments offer unique training opportunities, particularly for training astronauts and preadapting them to the novel sensory conditions of microgravity. Two unresolved human factors issues in virtual reality (VR) systems are: 1) potential "cybersickness", and 2) maladaptive sensorimotor performance following exposure to VR systems. Interestingly, these aftereffects are often quite similar to adaptive sensorimotor responses observed in astronauts during and/or following space flight. Changes in the environmental sensory stimulus conditions and the way we interact with the new stimuli may result in motion sickness, and perceptual, spatial orientation and sensorimotor disturbances. Initial interpretation of novel sensory information may be inappropriate and result in perceptual errors. Active exploratory behavior in a new environment, with resulting feedback and the formation of new associations between sensory inputs and response outputs, promotes appropriate perception and motor control in the new environment. Thus, people adapt to consistent, sustained alterations of sensory input such as those produced by microgravity, unilateral labyrinthectomy and experimentally produced stimulus rearrangements. Adaptation is revealed by aftereffects including perceptual disturbances and sensorimotor control disturbances. The purpose of the current study was to compare disturbances in postural control produced by dome and head-mounted virtual environment displays, and to examine the effects of exposure duration, and repeated exposures to VR systems. Forty-one subjects (21 men, 20 women) participated in the study with an age range of 21-49 years old. One training session was completed in order to achieve stable performance on the posture and VR tasks before participating in the experimental sessions. Three experimental sessions were performed each separated by one day. The subjects performed a navigation and pick and place task in either a dome or head-mounted display (HMD) VR system for either 30 or 60 min. The environment was a square room with 15 pedestals on two opposite walls. The objects appeared on one set of pedestals and the subject s objective was to move the objects to the other set of pedestals. After the subject picked up an object, a pathway appeared and they were required to follow the pathway to the other side of the room. The subject was instructed to perform the task as quickly and accurately as possible, avoiding hitting walls and other any obstacles and placing the object on the center of the pedestal. Postural equilibrium was measured (using the Equitest CDP balance system, Neurocom, International) before, immediately after, and at 1 hr, 2 hr, 4 hr and 6 hr following exposure to VR. Postural equilibrium was measured during quiet stance with eyes open, eyes closed and vision and/or ankle proprioceptive inputs selectively altered by servo-controlling the visual surround and/or support surface to the subject s center of mass sway. Posture data was normalized using a log transformation and motion sickness data were normalized using the square root. In general, we found that exposure to VR resulted in decrements in postural stability. The largest decrements were observed in the tests performed immediately following exposure to VR and showed a fairly rapid recovery across the remaining test sessions. In addition, subjects generally showed improvement across days. We found significant main effects for day and time for the composite equilibrium score and for sensory organization tests (SOT) 1, 2 and 6. Significant main effects were observed for day for SOT 3 and 5. Although we found no significant main effects for gender (when center of gravity was used as a covariate), we did observe significant gender X time interaction effects for composite equilibrium and for SOT 1, 3, 4 and 5. Women appeared to show larger decrements in postural stability immediately after exposure to VR than men, but recover more quickly than n. Finally, we found no significant main effects for type of VR device or for exposure duration, however, these factors did interact with other factors during some of the SOTs. Subjects exhibited rapid recovery of motion sickness symptoms across time following exposure to VR and significantly less severe symptoms across days. We did not observe main effects for gender, type of device or duration of exposure. Individuals recovered from the detrimental effects of exposure to virtual reality on postural control and motion sickness within one hour. Sickness severity and initial decrements in postural equilibrium decreases over days, which suggests that subjects become dual-adapted over time. These findings provide some direction for developing training schedules for VR users that facilitate adaptation, and support the idea that preflight training of astronauts may serve as useful countermeasure for the sensorimotor effects of space flight.

Harm, D. L.↗

NASA NTRS2008

Assimilation of Aura Ozone Data and Comparisons with In Situ Observations

Ozone data from the Ozone Monitoring Instrument (OMI) and the Microwave Limb Sounder (MLS) onboard EOS Aura satellite were assimilated into the Goddard Earth Observing System Version 4 (GEOS-4) ozone assimilation system. Comparison of assimilated ozone with ozone sonde and MOZAIC data indicate an agreement within 10% in the lower stratosphere, where dynamical processes dominate. Assimilation of OMI and MLS data improves tropospheric column estimates in the Atlantic region, but leads to an overestimation in the tropical Pacific in comparison with SHADOZ sondes. Transport and data biases are considered in order to understand these discrepancies. Comparisons of assimilated tropospheric ozone columns with ozone sonde data reveal root-mean-square (RMS) differences of 2.9 to 7.2 DU, which are typically smaller than the model-sonde RMS differences. Four different definitions of the tropopause using temperature lapse rate, potential vorticity (PV) and isentropic surfaces or ozone isosurfaces are compared with respect to their global impact on the estimated tropospheric ozone column. The largest sensitivity in the tropospheric ozone column is found near the subtropical jet, where the ozone or PV determined tropopause typically lies below the lapse rate tropopause.

Stajner, Ivanka↗

DOE OSTI2023

How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the U.S. Midwest?

Cropland carbon budget depicts the amount of carbon flowing in and out of agroecosystems and the changes in carbon stocks of soil and living biomass during the same period. Soil carbon credit is the additional change in soil carbon stock under certain farming practices compared with the business-as-usual practices. Accurately calculating cropland carbon budget and soil carbon credit is critical to assessing climate change mitigation potential in agroecosystems. The calculation of cropland carbon budget and soil carbon credit is sensitive to local soil and climatic conditions, especially initial soil organic carbon (SOC) stock, which is determined by both SOC concentration (SOC%) and bulk density (Bulk_Density). SOC stock data are either from soil sampling or gridded public survey data. In agroecosystem models, SOC stock data are a key model input for quantifying cropland carbon budget and soil carbon credit. However, various types and degrees of uncertainties exist in SOC stock datasets, which propagate to the quantification of SOC stock change. In particular, a large discrepancy is found in two widely used SOC stock datasets — Rapid Carbon Assessment dataset (RaCA) and Gridded Soil Survey Geographic Database (gSSURGO) — in the U.S. Midwest, with a relative difference (quantified using Normalized Root Mean Square Error, NRMSE) of 48.0% for 0–30 cm SOC stock between the two datasets. It remains largely unclear how uncertainty in SOC stocks affects the calculation of cropland carbon budget and soil carbon credit. To address this question, we used a well-validated process-based agroecosystem model, ecosys, to assess the impacts of SOC stock uncertainty on carbon budget and soil carbon credit calculation in the U.S. Midwestern corn-soybean rotation systems. Our results reveal the following findings: (1) A sizable discrepancy exists in simulated cropland carbon budget between using gSSURGO and using RaCA for their SOC% and Bulk_Density as model inputs, with a Pearson correlation coefficient (r) of only 0.4 for simulated change of SOC stock (ΔSOC) using these two different soil datasets. (2) Simulated cropland carbon budget components were more sensitive to initial SOC% than to Bulk_Density. For example, the upper and lower quartiles of multi-year averaged ΔSOC were –29.8 and 4.8 gC/m 2 /year for the selected counties respectively, with an uncertainty of 13.7 and 0.7 gC/m 2 /year induced by uncertainties in initial SOC% and Bulk_Density, respectively. (3) Both simulated ΔSOC and its uncertainty were negatively correlated with initial SOC%, whereas ΔSOC was negatively correlated with air temperature, and ΔSOC uncertainty was positively correlated with air temperature. (4) The uncertainty of calculated soil carbon credits was much smaller compared with the uncertainty of calculated absolute carbon budgets assuming the same SOC stock uncertainty level in the inputs. Specifically, in our assessment comparing planting cover crops vs no cover crop, the uncertainty of calculated soil carbon credits induced by initial SOC% uncertainty was less than 4% (relative to the quantified value of the soil carbon credits) for 90% of the cases. Our analysis highlights that high accuracy measurement of SOC% as inputs is needed for the calculation of cropland carbon budgets; however, soil carbon credit quantification is much less sensitive to the initial SOC% inputs, and the current publicly available soil datasets (e.g., gSSURGO) are largely suitable for the calculation of soil

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Changing Interactions Between Trace Gas Fluxes, Belowground Chemistry, and Plant Traits Across an Arctic Thermokarst Landscape

Arctic permafrost soils are increasingly subject to thermokarst that is, abrupt ground subsidence caused by thaw. Wetlands can form within these depressions, leading to changes in organic matter decomposition and gas fluxes (CO 2 , CH 4 , N 2 O, NH 3 ). Thermokarst wetlands tend to be dominated by graminoids, while surrounding upland tussock tundra tends to be dominated by mixed communities of shrubs and graminoids. Here, to investigate how thermokarst alters the land-atmosphere exchange of C and N gases in Arctic tundra, we analyzed soil, porewater, above- and belowground biomass, and measured gas fluxes across dominant plant functional types (PFTs) within a lowland thermokarst wetland and adjacent upland tussock tundra. Both locations were overall sinks of CO 2 , sources of CH 4 , and sources of both N 2 O and NH 3 . We found that thermokarst wetlands emitted enough CH 4 to generate a positive radiative forcing in CO 2 equivalents (+1.2 μmol m −2 s −1 CO 2 -eq), counteracting the high CO 2 uptake. In contrast, the upland tussock tundra had a net negative radiative forcing (−1.2 μmol m −2 s −1 CO 2 -eq). Differences in gas flux and soil chemistry between upland and lowland are primarily driven by flooded conditions present in thermokarst wetland. Additionally, root biomass from graminoids across both lowlands and uplands significantly correlated with CH 4 fluxes, supporting previous observations of plant-mediated transport of CH 4 . Graminoid cover was correlated with increases in low molecular weight dissolved organic carbon, possibly associated with root exudates that fuel methanogenesis. Forb cover in the upland tussock tundra was significantly correlated with nine soil chemical variables, indicating that forbs may influence local soil chemistry or conversely, that soil chemistry controls where forbs grow. Overall, our findings indicate the variability in gas fluxes in the upland tussock tundra is partially controlled by PFT cover, while thermokarst wetlands emit enough CH 4 to counteract CO 2 uptake, with implications for carbon budget changes in Arctic systems.

Land-atmosphere feedback↗

DOE OSTI2025

Intermodal microwave-to-optical transduction using silicon-on-sapphire optomechanical ring resonator

Optomechanical and electro-optomechanical systems have emerged as one of the most promising approaches for quantum microwave-to-optical transduction to interconnect distributed quantum modalities for scaling the quantum systems. These systems use suspended structures to increase mode overlap and mitigate loss to achieve high efficiency. However, the suspended design’s poor heat dissipation under strong drive limits the ultimate efficiency. Here, we demonstrate an unsuspended optomechanical ring resonator (OMR) based on the silicon-on-sapphire (SOS) platform for microwave-to-optical frequency conversion. The OMR achieves a triply resonant optical-to-optical conversion with an enhanced coupling rateG b = 3.6 gigahertz per square-root milliwatt at a peak conversion efficiency of 1.2% with 3.6-milliwatt microwave drive power and a microwave-to-optical conversion efficiency of 1.5 × 10 −5 at 10-milliwatt optical drive power. Our results show that the unsuspended SOS platform, which mitigates the thermal effect and is compatible with superconducting qubits, is a promising platform for optomechanical circuitry and quantum transduction.

Science & Technology - Other Topics↗

DOE OSTI2020

Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response

Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1°C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2°C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3°C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23°C(±0.12°C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1985

A Residuals Approach to Filtering, Smoothing and Identification for Static Distributed Systems

An approach for state estimation and identification of spatially distributed parameters embedded in static distributed (elliptic) system models is advanced. The method of maximum likelihood is used to find parameter values that maximize a likelihood functional for the system model, or equivalently, that minimize the negative logarithm of this functional. To find the minimum, a Newton-Raphson search is conducted that from an initial estimate generates a convergent sequence of parameter estimates. For simplicity, a Gauss-Markov approach is used to approximate the Hessian in terms of products of first derivatives. The gradient and approximate Hessian are computed by first arranging the negative log likelihood functional into a form based on the square root factorization of the predicted covariance of the measurement process. The resulting data processing approach, referred to here by the new term of predicted data covariance square root filtering, makes the gradient and approximate Hessian calculations very simple. A closely related set of state estimates is also produced by the maximum likelihood method: smoothed estimates that are optimal in a conditional mean sense and filtered estimates that emerge from the predicted data covariance square root filter.

Rodriguez, G.↗