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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrated Spatial, Spectral, & Temporal Optical Reflectance System for Precision Occupancy & Location Sensing to Improve Building Energy Efficiency

Buildings consume approximately 35% of the electricity used in the U.S. and building owners can significantly reduce this energy use by providing services like heating, electrical power and lighting only when people are present. The ARPAe funded program titled “INTEGRATED SPATIAL, SPECTRAL, & TEMPORAL OPTICAL REFLECTANCE SYSTEM FOR PRECISION OCCUPANCY & LOCATION SENSING TO IMPROVE BUILDING ENERGY EFFICIENCY” demonstrates how a low cost sensor technology developed for measuring distances can be used to count and locate occupants with a high degree of precision with a very low error rates. This platform tells a building control system where occupants are located (but not who they are) so that energy consuming services can be provided only when the services are needed by building occupants. The original proof of concept involved using low cost, commercially available time-of-flight (TOF) sensors that measure distance, but the performance of these existing sensors was lacking, as they could not operate properly in the presence of sunlight, which blinded the simple TOF sensors and limited their utility in buildings. This project proposed a powerful new class of TOF sensors that used state-of-the-art integrated circuit (IC) fabrication processes that combined advanced photonics with conventional silicon chip circuitry for improved sensor performance. An equally important part of this project was to find ways to maximize occupant count and location accuracy while using the fewest number of sensors possible, in order to keep costs low. By using building blueprints to create digital twins of commercial building spaces, the team developed new algorithms to maximize occupant count and tracking accuracy by properly locating the minimum number of sensors at just the right spots in the building. This capability not only minimizes system costs but also simplified sensor installation and system commissioning. Our simulations of our sensor networks for a range of commercial floorplan designs demonstrated that our installed cost target of $0.08/sqft was attainable, though not fully demonstrated during the project. Finally, we noted that the TOF sensor concept could provide a valuable role in health and eldercare by tracking patients without the need for worn sensors and would be useful for fall detection and other patient safety metrics, including tracking healthcare/patient interactions. We feel that, when fully developed, this new class of sophisticated TOF sensors and support software will be a powerful new approach to improving building energy efficiency based on occupant centric control platforms and will also open new levels of patient safety in healthcare operations. To realize this potential, the team formed the Troy Sensor Company LLC to oversee licensing of the programs patents and continue to seek commercialization of this program’s activity sensing technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data

Lakes provide critical water resources for human activities and ecosystems, particularly in the Mongolian Plateau (MP), which is characterized by a dry climate and a harsh environment. As a region that is sensitive to anthropogenic warming, tracking lake surface water temperature (LSWT) changes in Mongolian lakes is crucial for understanding the consequences of a warming climate on lake ecosystems. However, the long-term monitoring of LSWT is restricted by the spatiotemporal gaps in the raw imagery of remote sensing-based land surface temperature (LST), e.g., the commonly used Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. This study applied an improved gap-filling method by utilizing the discrete cosine transform-based penalized least squares (DCT-PLS) strategy in the spatial domain combined with the linear interpolation (LI) algorithm in the temporal domain. The method was applied to fill gaps in the LSWT imagery of 12 representative lakes across MP. The randomly sampled high-quality MODIS LSWT values in the spatial and temporal domains were excavated as false data gaps and considered “virtual true” validation datasets. The spatial validation results showed that the estimated LSWT for all the lake cases were comparable with the “virtual true” LSWT values, with the average values of the coefficient of determination, mean absolute error, mean square error, and root mean square error being 0.98, 0.38 °C, 0.45 °C, and 0.59 °C, respectively. Meanwhile, the error of nighttime LSWT results was relatively lower than that of daytime LSWT. For temporal interpolation validation, the LI algorithm exhibited relatively better performance and could more objectively indicate the variation in LSWT. Benefiting from the spatially and temporally well-constrained data, we analyzed the interannual and intra-annual change characteristics of the LSWTs of the 12 lakes. The long-term variations of annual and seasonal mean LSWTs in the 12 selected lakes exhibited no evident trends in 2000–2020, while presented apparent interannual fluctuations. The slight changes in the average LSWTs of the 12 selected lakes were in excellent synchronization with the surrounding LST derived from the reanalysis datasets, confirming the widely reported phenomenon of “global warming hiatus” that occurred in the early 21st century. This study improves the understanding of the LSWT variations in Mongolian lakes in response to global climate change. It has the potential to provide an effective approach for monitoring LSWT changes in other large-scale studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Preliminary Examination of Ethanol Fuel Effects on EPA’s R-factor for Vehicle Fuel Economy

The U.S. Department of Energy (DOE) supported a test program from 2007 through 2012 to evaluate the potential impacts of intermediate ethanol blends (also known as mid-level blends) on legacy vehicles and other engines. The purpose of the program was to assess the viability of using intermediate ethanol blends as a contributor to meeting national goals for the use of renewable fuels. Appendix A lists a bibliography of related studies. The catalyst durability program involved aging and emissions testing vehicles on a range of ethanol blends. The study was completed in 2011 and a final report issued shortly after. This report describes a preliminary analysis of the fuel economy data from the catalyst durability study, to determine the proper value for the R factor which is called out in the Code of Federal Regulations (CFR) for computing vehicle fuel economy on the certification cycle. The fuel economy equation that is specified in CFR for gasoline-fuelled vehicles is based on a carbon mass balance (CMB) approach to determine the amount of fuel consumed during the test by measuring the carbon-bearing emissions that are produced; however, it also incorporates a scaling factor (R factor) based on the net heating value of the fuel and the sensitivity of fuel economy to changes in the heating value. The impact of the R factor is a fixed ratio in the resultant fuel economy that is dependent upon fuel properties other than those required for a typical CMB calculation. This equation was put in place in 1988 to correct for differences between certification fuels to address corporate average fuel economy (CAFE) credit issues associated with fuel property variations. The algorithm adjusts the calculated fuel economy to compute what would have been measured had the 1975 certification fuel been used for the test. The R factor was defined as the sensitivity of the fuel economy result to changes in fuel energy content. When R equals 1.0, the fuel economy change exactly tracks the energy density difference between the fuels. If R is less than 1.0, the fuel economy change is smaller than the change in energy density. The R factor was defined to be 0.6 based on tests using 1980s vehicles. Since that time, the Auto/Oil test program has established that the R factor for 1990s vehicles is higher (about 0.93). More recently EPA analyzed the EPAct/V2/E-89 dataset to compute the R factor, resulting in an average of 0.82 to 0.86. It is important to note that the EPAct/V2/E89 test program used the LA92 test cycle, a cycle known to contain more aggressive accelerations than the FTP. To date, EPA has only required emissions and fuel economy testing of gasoline vehicles with a certification fuel that does not contain ethanol. However in 2013 EPA issued a Proposed Rule seeking comment on the establishment of an emissions certification fuel containing ethanol, such as E10 or E15. Calculating modern vehicle fuel economy with the existing CFR equation with an R factor of 0.6 when ethanol blends are used produces significant errors. For the catalyst durability program, a straightforward CMB approach was used to compute fuel economy, thereby allowing a straightforward evaluation of the impact of ethanol content on fuel economy. However, if an ethanol-containing fuel is to become the new certification fuel for light-duty vehicles, consistent application of the CFR equation needs to be considered for the benefit of manufacturers’ CAFE compliance. Analysis of city cycle Federal Test Procedure (FTP) fuel economy test results and fuel analyses from the catalyst durability study indicates that the average R-factor for modern vehicles is very close to unity at about 0.94±0.04. This result is very similar to the results of the 1993 Auto/Oil test program. Future work should examine other drive cycles, and advanced vehicle technologies which may reveal sensitivities to properties other than heating value.

intermediate ethanol blends↗
DOE OSTI2024

Shortwave Array Spectroradiometer-Hemispheric (SAS-He): design and evaluation

A novel ground-based radiometer, referred to as the Shortwave Array Spectroradiometer-Hemispheric (SAS-He), is introduced. This radiometer uses the shadow-band technique to report total irradiance and its direct and diffuse components frequently (every 30 s) with continuous spectral coverage (350–1700 nm) and moderate spectral (~2.5 nm ultraviolet–visible and ~6 nm shortwave-infrared) resolution. The SAS-He's performance is evaluated using integrated datasets collected over coastal regions during three field campaigns supported by the US Department of Energy's Atmospheric Radiation Measurement (ARM) program, namely the (1) Two-Column Aerosol Project (TCAP; Cape Cod, Massachusetts), (2) Tracking Aerosol Convection Interactions Experiment (TRACER; in and around Houston, Texas), and (3) Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE; La Jolla, California). We compare (i) aerosol optical depth (AOD) and total optical depth (TOD) derived from the direct irradiance, as well as (ii) the diffuse irradiance and direct-to-diffuse ratio (DDR) calculated from two components of the total irradiance. As part of the evaluation, both AOD and TOD derived from the SAS-He direct irradiance are compared to those provided by a collocated Cimel sunphotometer (CSPHOT) at five (380, 440, 500, 675, 870 nm) and two (1020, 1640 nm) wavelengths, respectively. Additionally, the SAS-He diffuse irradiance and DDR are contrasted with their counterparts offered by a collocated multifilter rotating shadowband radiometer (MFRSR) at six (415, 500, 615, 675, 870, 1625 nm) wavelengths. Overall, reasonable agreement is demonstrated between the compared products despite the challenging observational conditions associated with varying aerosol loadings and diverse types of aerosols and clouds. For example, the AOD- and TOD-related values of root mean square error remain within 0.021 at 380, 440, 500, 675, 870, 1020, and 1640 nm wavelengths during the three field campaigns.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

TU-H-206-07: Assessment of Geometric Distortion in EPI with a SPAMM Tagged Acquisition

Purpose: Echo planar imaging (EPI) is known to exhibit gross geometric distortion caused by multiple factors, including B0 inhomgeneity and transient eddy currents. However, diffusion weighted (DW) EPI has become indispensable for diagnosis and therapy assessment. We propose a methodology for quantifying distortion in EPI sequences that does not require the use of dedicated spatial accuracy phantoms, enabling flexibility in phantom design for QA of distortion effects in EPI protocols. Methods: The proposed methodology utilizes a saturation technique known as Spatial Modulation of Magnetization (SPAMM) that tags the imaging subject with saturated grid lines. Originally intended for tracking cardiac motion, these grids are applied to assess differences between diffusion weighting directions and b-values, or against a more geometrically robust sequence such as fast spin echo (FSE). The saturation preparation sequence consists of binomially weighted (e.g. 1-3-3-1) pulses interleaved with gradient blips along the frequency encode direction, followed by the same sequence with gradient blips in the phase encode direction. Three phantoms were assessed with these sequences: a spherical head-sized phantom, a large shimming phantom, and a modified PET ACR phantom that included compartments of water, air, oil, and Teflon. Each phantom was acquired with three sequences using parameters from a clinically appropriate protocol (22 cm head or 46 cm abdomen): a conventional DW-EPI sequence (3 DW directions), and both the DW-EPI and FSE sequences with tagging. Differences in grid locations were visualized with minimum intensity projection between images, and measured using intersecting locations on the grids. Results: Grid lines were clearly visualized on tagged images and enabled quantification of distortions. Maximum eddy current induced errors of 10.8 to 14.8 mm were observed in areas away from isocenter with DW gradients applied in various directions. Conclusion: SPAMM tagging provides a promising mechanism for assessing spatial distribution of distortion in EPI sequences.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Gamma-Ray Imaging to Monitor Accumulating Holdup

Over time, nuclear materials can accumulate in process equipment and keeping track of such material is of interest to many stakeholder communities including safeguards, process monitoring, criticality safety, and radiological safety. Passive gamma-ray imaging provides a visual and quantitative tool that can be applied to this problem, allowing one to determine the amount of material present from the images. In this work we emulate the accumulation of highly enriched uranium (HEU) in a large rectangular stainless-steel duct by stacking 5, 27 × 50 cm2 cards, each of which has approximately 11 g of 235U in oxide form distributed across its surface, behind each other. A series of images were collected using a coded-aperture gamma-ray imager, starting with a single card, adding a second card, etc. Long integrations were collected to allow evaluating the performance of the approach as a function of integration time. The images are analyzed using first principles to determine the amount of material in each image. The results are compared to the known amount of material in each configuration, and as a function of time. The analysis includes a first-principles error propagation and to further evaluate the uncertainty, a boot-strap sampling approach is also applied to the data. The work offers a proof of concept for unattended monitoring of uranium holdup with a quantitative gamma-ray imaging technique.

Ziock, Klaus-Peter↗
DOE OSTI2021

Solar Transposition Modeling via Deep Neural Networks With Sky Images

This article presents a notable advance toward the development of a new method of increasing the single-axis tracking photovoltaic (PV) system power output by improving the determination and near-term prediction of the optimum module tilt angle. The tilt angle of the plane receiving the greatest total irradiance changes with Sun position and atmospheric conditions including cloud formation and movement, aerosols, and particulate loading, as well as varying albedo within a module's field of view. In this article, we present a multi-input convolutional neural network that can create a profile of plane-of-array irradiance versus surface tilt angle over a full 180° arc from horizon to horizon. As input, the neural network uses the calculated solar position and clear-sky irradiance values, along with sky images. The target irradiance values are provided by the multiplanar irradiance sensor (MPIS). In order to account for varying irradiance conditions, the MPIS signal is normalized by the theoretical clear-sky global horizontal irradiance. Using this information, the neural network outputs an N -dimensional vector, where N is the number of points to approximate the MPIS curve via Fourier resampling. The output vector of the model is smoothed with a Gaussian kernel to account for error in the downsamping and subsequent upsampling steps, as well as to smooth the unconstrained output of the model. Furthermore, these profiles may be used to perform near-term prediction of angular irradiance, which can then inform the movement of a PV tracker.

42 ENGINEERING↗
DOE OSTI2021

The Initial–Final Mass Relation for Hydrogen-deficient White Dwarfs

The initial–final mass relation represents the total mass lost by a star during the entirety of its evolution from the zero age main sequence to the white-dwarf cooling track. The semiempirical initial–final mass relation (IFMR) is largely based on observations of DA white dwarfs, the most common spectral type of white dwarf and the simplest atmosphere to model. We present a first derivation of the semiempirical IFMR for hydrogen-deficient (non-DA) white dwarfs in open star clusters. We identify a possible discrepancy between the DA and non-DA IFMRs, with non-DA white dwarfs ≈0.07 M {sub ⊙} less massive at a given initial mass. Such a discrepancy is unexpected based on theoretical models of non-DA formation and observations of field white dwarf mass distributions. If real, the discrepancy is likely due to enhanced mass loss during the final thermal pulse and renewed post-AGB evolution of the star. However, we are dubious that the mass discrepancy is physical and instead is due to the small sample size, to systematic issues in model atmospheres of non-DAs, and to the uncertain evolutionary history of Procyon B (spectral type DQZ). A significantly larger sample size is needed to test these assertions. In addition, we also present Monte Carlo models of the correlated errors for DA and non-DA white dwarfs in the initial–final mass plane. We find the uncertainties in initial–final mass determinations for individual white dwarfs can be significantly asymmetric, but the recovered functional form of the IFMR is grossly unaffected by the correlated errors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SU-G-IeP3-12: Preliminary Report On the Experience of Patient Radiation Dose Monitoring and Tracking Systems; PEMNET, Radimetrics and DoseWatch

Purpose: Three patient radiation dose monitoring and tracking (PRDMT) systems have been in operation at this institution for the past 6 months. There are useful information that should be disseminated to those who are considering installation of PRDMT programs. In addition, there are “problems” uncovered in the process of estimating fluoroscopic “peak” skin dose (PSD), especially, for those patients who received interventional angiographic studies and in conjunction with surgical procedures. Methods: Upon exporting the PRDMT data to Microsoft Excel program, the peak skin dose can be estimated by applying various correction factors including; attenuation due to the tabletop and examination mattress, table height, tabletop translation, backscatter, etc. A procedure was established to screen and divide the PRDMT reported radiation dose and estimated PSD to three different levels of threshold to assess the potential skin injuries, to assist patient follow-up, risk management and provide radiation dosimetry information in case of “Sentinel Event”. Results: The Radiation Dose Structured Report (RDSR) was found to be the prerequisite for the PRDMT systems to work seamlessly. And, the geometrical parameters (gantry and table orientation) displayed by the equipment are not necessarily implemented in the “patient centric” manner which could result in a large error in the PSD estimation. Since, the PRDMT systems obtain their pertinent data from the DICOM tags including the polarity (+ and − signs), the geometrical parameters need to be verified. Conclusion: PRDMT systems provide a more accurate PSD estimation than previously possible as the air-kerma-area dose meter become widely implemented. However, care should be exercised to correctly apply the geometrical parameters in estimating the patient dose. In addition, further refinement is necessary for these software programs to account for all geometrical parameters such as the tabletop translation in the z-direction in particular.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-255: Accuracy and Precision of Dynamic Tracking Irradiation with VERO-4DRT System

Purpose: The VERO-4DRT system is able to provide dynamic tracking irradiation (DTI) for the target with respiratory motion. This technique requires enough commissioning for clinical implementation. The purpose of this study is to make sure the accuracy and precision of DTI using VERO- 4DRT through commissioning from fundamental evaluation to end-to-end test. Method: We evaluated several contents for DTI commissioning: the accuracy of absorption dose at isocenter in DTI, the field size and penumbra of DTI, the accuracy of 4D modeling in DTI. All evaluations were performed by respiratory motion phantom (Quasar phantom). These contents were compared the results between static irradiation and DTI. The shape of radiation field was set to square from 3 cm × 3 cm to 10 cm × 10 cm. The micro 3D chamber and Gafchromic EBT3 film were used for absorbed dose and relative dose distribution measurement, respectively. The sine and irregular shaped waves were used for demonstrative respiratory motion. The visicoil was implanted into the phantom for guidance of respiratory motion. The respiration patterns of frequency and motion amount were set to 10–15 BPM and 1–2 cm, respectively. Results: As the result of absorbed dose of DTI in comparison with static irradiation, the average dose error at isocenter was 0.5% even though various respiratory patterns were set on. As the result of relative dose distribution, the field size (set it on 50% dose line) was not significantly changed in all respiratory patterns. However, the penumbra was larger in greater respiratory motion (up to 4.1 mm). The 4D modeling coincidence between actual and created waves was within 1%. Conclusion: The DTI using VERO-4DRT can provide sufficient accuracy and precision in absorbed dose and distribution. However, the patientspecific quantitative internal margin corresponding respiratory motion should be taken into consideration with image guidance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Effectiveness of external respiratory surrogates for in vivo liver motion estimation

Purpose: Due to low frame rate of MRI and high radiation damage from fluoroscopy and CT, liver motion estimation using external respiratory surrogate signals seems to be a better approach to track liver motion in real-time for liver tumor treatments in radiotherapy and thermotherapy. This work proposes a liver motion estimation method based on external respiratory surrogate signals. Animal experiments are also conducted to investigate related issues, such as the sensor arrangement, multisensor fusion, and the effective time period. Methods: Liver motion and abdominal motion are both induced by respiration and are proved to be highly correlated. Contrary to the difficult direct measurement of the liver motion, the abdominal motion can be easily accessed. Based on this idea, our study is split into the model-fitting stage and the motion estimation stage. In the first stage, the correlation between the surrogates and the liver motion is studied and established via linear regression method. In the second stage, the liver motion is estimated by the surrogate signals with the correlation model. Animal experiments on cases of single surrogate signal, multisurrogate signals, and long-term surrogate signals are conducted and discussed to verify the practical use of this approach. Results: The results show that the best single sensor location is at the middle of the upper abdomen, while multisurrogate models are generally better than the single ones. The estimation error is reduced from 0.6 mm for the single surrogate models to 0.4 mm for the multisurrogate models. The long-term validity of the estimation models is quite satisfactory within the period of 10 min with the estimation error less than 1.4 mm. Conclusions: External respiratory surrogate signals from the abdomen motion produces good performance for liver motion estimation in real-time. Multisurrogate signals enhance estimation accuracy, and the estimation model can maintain its accuracy for at least 10 min. This approach can be used in practical applications such as the liver tumor treatment in radiotherapy and thermotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Deep Learning Experiments for Tropical Cyclone Intensity Forecasts

Reducing tropical cyclone (TC) intensity forecast errors is a challenging task that has interested the operational forecasting and research community for decades. To address this, we developed a deep learning (DL)-based multilayer perceptron (MLP) TC intensity prediction model. The model was trained using the global Statistical Hurricane Intensity Prediction Scheme (SHIPS) predictors to forecast the change in TC maximum wind speed for the Atlantic basin. In the first experiment, a 24-h forecast period was considered. To overcome sample size limitations, we adopted a leave one year out (LOYO) testing scheme, where a model is trained using data from all years except one and then evaluated on the year that is left out. When tested on 2010–18 operational data using the LOYO scheme, the MLP outperformed other statistical–dynamical models by 9%–20%. Additional independent tests in 2019 and 2020 were conducted to simulate real-time operational forecasts, where the MLP model again outperformed the statistical–dynamical models by 5%–22% and achieved comparable results as HWFI. The MLP model also correctly predicted more rapid intensification events than all the four operational TC intensity models compared. In the second experiment, we developed a lightweight MLP for 6-h intensity predictions. When coupled with a synthetic TC track model, the lightweight MLP generated realistic TC intensity distribution in the Atlantic basin. Therefore, the MLP-based approach has the potential to improve operational TC intensity forecasts, and will also be a viable option for generating synthetic TCs for climate studies.

58 GEOSCIENCES↗
DOE OSTI2012

Incidence of Changes in Respiration-Induced Tumor Motion and Its Relationship With Respiratory Surrogates During Individual Treatment Fractions

Purpose: To determine how frequently (1) tumor motion and (2) the spatial relationship between tumor and respiratory surrogate markers change during a treatment fraction in lung and pancreas cancer patients. Methods and Materials: A Cyberknife Synchrony system radiographically localized the tumor and simultaneously tracked three respiratory surrogate markers fixed to a form-fitting vest. Data in 55 lung and 29 pancreas fractions were divided into successive 10-min blocks. Mean tumor positions and tumor position distributions were compared across 10-min blocks of data. Treatment margins were calculated from both 10 and 30 min of data. Partial least squares (PLS) regression models of tumor positions as a function of external surrogate marker positions were created from the first 10 min of data in each fraction; the incidence of significant PLS model degradation was used to assess changes in the spatial relationship between tumors and surrogate markers. Results: The absolute change in mean tumor position from first to third 10-min blocks was >5 mm in 13% and 7% of lung and pancreas cases, respectively. Superior-inferior and medial-lateral differences in mean tumor position were significantly associated with the lobe of lung. In 61% and 54% of lung and pancreas fractions, respectively, margins calculated from 30 min of data were larger than margins calculated from 10 min of data. The change in treatment margin magnitude for superior-inferior motion was >1 mm in 42% of lung and 45% of pancreas fractions. Significantly increasing tumor position prediction model error (mean {+-} standard deviation rates of change of 1.6 {+-} 2.5 mm per 10 min) over 30 min indicated tumor-surrogate relationship changes in 63% of fractions. Conclusions: Both tumor motion and the relationship between tumor and respiratory surrogate displacements change in most treatment fractions for patient in-room time of 30 min.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water‐Tagging Enabled Hydrologic Models

Determining the age distribution of water exiting a catchment is important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages, yet forward modeling of individual events may not systematically capture the full transit time distribution (TTD). Here, we present a “sequential precipitation input tagging” (SPIT) framework to tag all input precipitation at regular intervals during extended model simulations. Monthly tags over 7 years were applied at six National Ecological Observatory Network sites to calculate TTDs and derive mean virtual tracer age, $\overline{T_{V}}$, fractions of young water, F yw , and hydrologic tracer concentrations (water isotopes δ 18 O and δ 2 H) within a tagging enabled version of the Weather Research and Forecast hydrologic model (WRF-Hydro). Throughout seven simulation years, the fraction of simulated discharge derived from tagged events, F tag , increased each year, with the final year's F tag ranging from 66% to 100% and highlights the need to apply SPIT over many years to understand TTDs. When the F tag was >75%, simulated $\overline{T_{V}}$ ranged 179–923 days and F yw 0.6%–23.9%, with daily values exhibiting a power-law relationship with precipitation, discharge, and groundwater. Through implementation of SPIT, we find this hydrologic model configuration performs poorly in estimation of $\overline{T_{V}}$ and F yw (root mean squared error of 469 days and 14.4% respectively), suggesting it misrepresents subsurface mixing. Thus, the SPIT framework provides a reproducible approach to calculate watershed transit times within tagging enabled models and thereby assess and improve representation of hydrologic processes.

fraction of young water↗
DOE OSTI2012

Target Strength of Southern Resident Killer Whales (Orcinus orca): Measurement and Modeling

A major criterion for tidal power licensing in Washington’s Puget Sound is the management of the risk of injury to killer whales due to collision with moving turbine blades. An active monitoring system is being proposed for killer whale detection, tracking, and alerting that links to and triggers temporary turbine shutdown when there is risk of collision. Target strength (TS) modeling of the killer whale is critical to the design and application of any active monitoring system. A 1996 study performed a high-resolution measurement of acoustic reflectivity as a function of frequency of a female bottlenose dolphin (2.2 m length) at broadside aspect and TS as a function of incident angle at 67 kHz frequency. Assuming that killer whales share similar morphology structure with the bottlenose dolphin, we extrapolated the TS of an adult killer whale 7.5 m in length at 67 kHz frequency with -8 dB at broadside aspect and -28 dB at tail side. The backscattering data from three Southern Resident killer whales were analyzed to obtain the TS measurement. These data were collected at Lime Kiln State Park using a split-beam system deployed from a boat. The TS of the killer whale at higher frequency (200 kHz) was estimated based on a three-layer model for plane wave reflection from the lung of the whale. The TS data of killer whales were in good agreement with our model. In this paper, we also discuss and explain possible causes for measurement estimation error.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Ion Mobility Separations Using Cocentric Architecture

Ion mobility separations are usually performed in linear channels, which, when extended, can have a large footprint. In this work, we explored the performance of an ion mobility device with a curved architecture which can have a more compact form. The Co-centric Ion Mobility Spectrometer (CIMS) works by manipulating ions between two co-centric surfaces, each containing a serpentine track. The mobility separation inside CIMS is achieved using traveling waveforms (TWs). We initially evaluated the device using ion trajectory simulations using SIMION, which indicated that when ions traveled circularly inside CIMS, they resulted in similar resolving powers and transmitted m/z range as traveling in a straight path in structures for lossless ion manipulations (SLIM). We then performed experimental validation of CIMS in conjunction with a TOF MS. The CIMS was made of 2 flexible printed circuit board materials folded into concentric cylinders separated by a gap of 2.8 mm. The device was about 50 mm diameter × 152 mm long and provided 1.846 m of serpentine path length. Three sets of mixtures (Agilent tune mixture, tetraalkylammonium salts, and 8 peptide mixture) and four traveling waveform profiles (square, sine, triangle, and sawtooth) were used. The sawtooth TW profile produced a slightly higher resolving power for the Agilent tuning mixture and tetraalkylammonium ions. The average resolving power for Agilent tune mixture ions ranged from 37 (using sawtooth TW) to 27 (using square TW). For tetraalkylammonium ions, the average resolving powers ranged from 45 (sawtooth TW) to 31 (square TW). For the peptide mixture ions, the resolving power was similar among the four TW profiles and ranged from 51 to 56. The average percent error in TW CCS for the peptide mixture ions ranged was about 0.4%. In conclusion, the new device showed promising results for a device made of a flexible printed circuit board material, but improvements are needed to further increase the resolving power.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

The G+M eclipsing binary V530 Orionis: a stringent test of magnetic stellar evolution models for low-mass stars

We report extensive photometric and spectroscopic observations of the 6.1 day period, G+M-type detached double-lined eclipsing binary V530 Ori, an important new benchmark system for testing stellar evolution models for low-mass stars. We determine accurate masses and radii for the components with errors of 0.7% and 1.3%, as follows: M {sub A} = 1.0038 ± 0.0066 M {sub ☉}, M {sub B} = 0.5955 ± 0.0022 M {sub ☉}, R {sub A} = 0.980 ± 0.013 R {sub ☉}, and R {sub B} = 0.5873 ± 0.0067 R {sub ☉}. The effective temperatures are 5890 ± 100 K (G1 V) and 3880 ± 120 K (M1 V), respectively. A detailed chemical analysis probing more than 20 elements in the primary spectrum shows the system to have a slightly subsolar abundance, with [Fe/H] = –0.12 ± 0.08. A comparison with theory reveals that standard models underpredict the radius and overpredict the temperature of the secondary, as has been found previously for other M dwarfs. On the other hand, models from the Dartmouth series incorporating magnetic fields are able to match the observations of the secondary star at the same age as the primary (∼3 Gyr) with a surface field strength of 2.1 ± 0.4 kG when using a rotational dynamo prescription, or 1.3 ± 0.4 kG with a turbulent dynamo approach, not far from our empirical estimate for this star of 0.83 ± 0.65 kG. The observations are most consistent with magnetic fields playing only a small role in changing the global properties of the primary. The V530 Ori system thus provides an important demonstration that recent advances in modeling appear to be on the right track to explain the long-standing problem of radius inflation and temperature suppression in low-mass stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

A GENERALIZED STOCHASTIC COLLOCATION APPROACH TO CONSTRAINED OPTIMIZATION FOR RANDOM DATA IDENTIFICATION PROBLEMS

We present a scalable, parallel mechanism for stochastic identification/control for problems constrained by partial differential equations with random input data. Several identification objectives will be discussed that either minimize the expectation of a tracking cost functional or minimize the difference of desired statistical quantities in the appropriate $L^p$ norm, and the distributed parameters/control can both deterministic or stochastic. Given an objective we prove the existence of an optimal solution, establish the validity of the Lagrange multiplier rule and obtain a stochastic optimality system of equations. The modeling process may describe the solution in terms of high dimensional spaces, particularly in the case when the input data (coefficients, forcing terms, boundary conditions, geometry, etc) are affected by a large amount of uncertainty. For higher accuracy, the computer simulation must increase the number of random variables (dimensions), and expend more effort approximating the quantity of interest in each individual dimension. Hence, we introduce a novel stochastic parameter identification algorithm that integrates an adjoint-based deterministic algorithm with the sparse grid stochastic collocation FEM approach. This allows for decoupled, moderately high dimensional, parameterized computations of the stochastic optimality system, where at each collocation point, deterministic analysis and techniques can be utilized. The advantage of our approach is that it allows for the optimal identification of statistical moments (mean value, variance, covariance, etc.) or even the whole probability distribution of the input random fields, given the probability distribution of some responses of the system (quantities of physical interest). Our rigorously derived error estimates, for the fully discrete problems, will be described and used to compare the efficiency of the method with several other techniques. Numerical examples illustrate the theoretical results and demonstrate the distinctions between the various stochastic identification objectives.

Webster, Clayton G↗