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At least 1,063 records · Page 59

Hands-Free Transcranial Color Doppler Probe

Current transcranial color Doppler (TCD) transducer probes are bulky and difficult to move in tiny increments to search and optimize TCD signals. This invention provides miniature motions of a TCD transducer probe to optimize TCD signals. The mechanical probe uses a spherical bearing in guiding and locating the tilting crystal face. The lateral motion of the crystal face as it tilts across the full range of motion was achieved by minimizing the distance between the pivot location and the crystal face. The smallest commonly available metal spherical bearing was used with an outer diameter of 12 mm, a 3-mm tall retaining ring, and 5-mm overall height. Small geared motors were used that would provide sufficient power in a very compact package. After confirming the validity of the basic positioning concept, optimization design loops were completed to yield the final design. A parallel motor configuration was used to minimize the amount of space wasted inside the probe case while minimizing the overall case dimensions. The distance from the front edge of the crystal to the edge of the case was also minimized to allow positioning of the probe very close to the ear on the temporal lobe. The mechanical probe is able to achieve a +/-20deg tip and tilt with smooth repeatable action in a very compact package. The enclosed probe is about 7 cm long, 4 cm wide, and 1.8 cm tall. The device is compact, hands-free, and can be adjusted via an innovative touchscreen. Positioning of the probe to the head is performed via conventional transducer gels and pillows. This device is amendable to having advanced software, which could intelligently focus and optimize the TCD signal.

Chin, Robert↗

QSPIN: A High Level Java API for Quantum Computing Experimentation

QSPIN is a high level Java language API for experimentation in QC models used in the calculation of Ising spin glass ground states and related quadratic unconstrained binary optimization (QUBO) problems. The Java API is intended to facilitate research in advanced QC algorithms such as hybrid quantum-classical solvers, automatic selection of constraint and optimization parameters, and techniques for the correction and mitigation of model and solution errors. QSPIN includes high level solver objects tailored to the D-Wave quantum annealing architecture that implement hybrid quantum-classical algorithms [Booth et al.] for solving large problems on small quantum devices, elimination of variables via roof duality, and classical computing optimization methods such as GPU accelerated simulated annealing and tabu search for comparison. A test suite of documented NP-complete applications ranging from graph coloring, covering, and partitioning to integer programming and scheduling are provided to demonstrate current capabilities.

Quantu↗

Developing Near Optimal Control Sequences for Chiller Plants with Water-side Economizers: A Case Study in a Warm and Marine Climate

Various advanced control sequences for chiller plants with water-side economizers (WSE) have been proposed in literature, but the optimization of those controls is limited. It is possible to maximize energy savings by developing near-optimal control sequences, which are dependent on several factors such as the load profile. To address these gaps, we first identify an advanced control sequence and three key control parameters for chiller plants with WSE. Next, optimizations are performed to minimize energy consumption for seven combinations of control parameters. A chiller plant with WSE system in a warm and marine climate is studied and two load profiles are considered. The system and controls are modeled using the Modelica Buildings library. The results show optimizing the selected control parameters can reduce energy consumption by up to 11% depending on the load profile. Specifically, optimizing the cooling tower efficiency threshold in the condenser water reset control can significantly reduce energy savings for the variable load profile by efficiently shifting the load from the cooling tower to the chiller. This paper provides practical guidance for developing near-optimal control sequences for chiller plant with WSE systems considering impacts such as the load profile.

chiller plant↗

PHYSICS-BASED AUTOMATED REASONING FOR HEALTH MONITORING: SENSOR SET SELECTION

This paper addresses the problem of how to select a sensor set for equipment health monitoring that meets the needs of advanced O&M tasks that target cost reduction. They include maintenance optimization and asset management for the existing fleet and near-autonomous operation as currently envisioned for advanced reactors. The method uses physics-based automated reasoning to provide for a more “explainable” diagnosis. The algorithm is described along with its implementation on a computational cluster. Preliminary results for application to a use case in the current fleet are described.

diagnosis↗

Space station propulsion: The advanced development program at Lewis

A reference configuration was established for the initial operating capability (IOC) station. The reference configuration has assumed hydrazine fueled thrusters as the propulsion system. This was to establish costing and as a reference for comparison when other propulsion systems are considered. An integral part of the plan to develop the Space Station is the advanced development program. The objective of this program is to provide advanced technology alternatives for the initial and evolutionary Space Station which optimize the system's functional characteristics in terms of performance, cost, and utilization. The portion of the Advanced Development Program that is concerned with auxiliary propulsion and the research and programmatic activities conducted are discussed.

Jones, R. E.↗

Space Station propulsion - The Advanced Development Program at Lewis

A reference configuration was established for the initial operating capability (IOC) station. The reference configuration has assumed hydrazine fueled thrusters as the propulsion system. This was to establish costing and as a reference for comparison when other propulsion systems are considered. An integral part of the plan to develop the Space Station is the advanced development program. The objective of this program is to provide advanced technology alternatives for the initial and evolutionary Space Station which optimize the system's functional characteristics in terms of performance, cost, and utilization. The portion of the Advanced Development Program that is concerned with auxiliary propulsion and the research and programmatic activities conducted are discussed.

Jones, R. E.↗

Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement

This work describes a blueprint for a process that accelerates progress in science by quantitatively answering the following question: What is the optimal combination of fundamental-science and application-driven experiments to maximally reduce pertinent data uncertainties? Answering this question entails solving a high-dimensional and complex optimization problem that is best solved with advanced statistic techniques often classified as machine learning. We apply this process within the framework of nuclear data with the aim to select an experiment combination that will reduce uncertainties in 239 Pu nuclear data for neutron energies between 1 and 600 keV. In this field, fundamental-physics driven data, called differential, look at one nuclear physics observable at a time. They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. The candidates for integral experiments are criticality measurements that were refined by a genetic algorithm to be maximally sensitive to 239 Pu fission cross sections in the desired energy range. Twenty-three candidate differential experiments were investigated and span multiple nuclear physics observables (e.g., total, capture cross sections) for isotopes appearing in the integral experiments. The optimal combination among these candidate experiments was investigated via generalized least squares fitting, augmented with Gaussian processes to ameliorate statistical irregularities in data, and the D-optimality criterion. The latter evaluates for each pair of candidates the joint reduction in uncertainties of all 12200 nuclear data appearing in the integral experiments compared to the knowledge we have from 168 past experiments, theory, and nuclear data. We chose as differential measurements those that investigate 63 Cu and 239 Pu total cross sections, based on D-optimality rank and feasibility constraints. Two integral (criticality) experiments were selected: An experiment with Al 2 ⁢O 3 and graphite interleaved with Pu and a thick Cu reflector explores 1–30 keV, while we target the 30–600 keV range with an experiment that swaps boron in place of graphite with a different geometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Neutron Characterization for Additive Manufacturing

Oak Ridge National Laboratory (ORNL) is leveraging decades of experience in neutron characterization of advanced materials together with resources such as the Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR) shown in Fig. 1 to solve challenging problems in additive manufacturing (AM). Additive manufacturing, or three-dimensional (3-D) printing, is a rapidly maturing technology wherein components are built by selectively adding feedstock material at locations specified by a computer model. The majority of these technologies use thermally driven phase change mechanisms to convert the feedstock into functioning material. As the molten material cools and solidifies, the component is subjected to significant thermal gradients, generating significant internal stresses throughout the part (Fig. 2). As layers are added, inherent residual stresses cause warping and distortions that lead to geometrical differences between the final part and the original computer generated design. This effect also limits geometries that can be fabricated using AM, such as thin-walled, high-aspect- ratio, and overhanging structures. Distortion may be minimized by intelligent toolpath planning or strategic placement of support structures, but these approaches are not well understood and often "Edisonian" in nature. Residual stresses can also impact component performance during operation. For example, in a thermally cycled environment such as a high-pressure turbine engine, residual stresses can cause components to distort unpredictably. Different thermal treatments on as-fabricated AM components have been used to minimize residual stress, but components still retain a nonhomogeneous stress state and/or demonstrate a relaxation-derived geometric distortion. Industry, federal laboratory, and university collaboration is needed to address these challenges and enable the U.S. to compete in the global market. Work is currently being conducted on AM technologies at the ORNL Manufacturing Demonstration Facility (MDF) sponsored by the DOE's Advanced Manufacturing Office. The MDF is focusing on R&D of both metal and polymer AM pertaining to in-situ process monitoring and closed-loop controls; implementation of advanced materials in AM technologies; and demonstration, characterization, and optimization of next-generation technologies. ORNL is working directly with industry partners to leverage world-leading facilities in fields such as high performance computing, advanced materials characterization, and neutron sciences to solve fundamental challenges in advanced manufacturing. Specifically, MDF is leveraging two of the world's most advanced neutron facilities, the HFIR and SNS, to characterize additive manufactured components.

Watkins, Thomas↗

Systems-Level Synthetic Biology for Advanced Biofuel Production

Cyanobacteria have been shown to be capable of producing a variety of advanced biofuels; however, product yields remain well below those necessary for large scale production. New genetic tools and high throughput metabolic engineering techniques are needed to optimize cyanobacterial metabolisms for enhanced biofuel production. Towards this goal, this project advances the development of a multiple promoter replacement technique for systems-level optimization of gene expression in a model cyanobacterial host: Synechococcus sp. PCC 7002. To realize this multiple-target approach, key capabilities were developed, including a high throughput detection method for advanced biofuels, enhanced transformation efficiency, and genetic tools for Synechococcus sp. PCC 7002. Moreover, several additional obstacles were identified for realization of this multiple promoter replacement technique. The techniques and tools developed in this project will help to enable future efforts in the advancement of cyanobacterial biofuels.

09 BIOMASS FUELS↗

Microcalorimeter Absorber Optimization for 0.2 to 12 keV X-Rays

The Advanced Telescope for High ENergy Astrophysics (ATHENA) mission requires high quantum efficiency (QE) x-ray absorption, >90.6% at 7 keV and low specific heat capacity, 0.731 pJ/K. The designed ATHENA x-ray absorbers are cantilevered square tiles (pitch of 317 microns) of 1.05 μm thick Au and 5.51 μm thick Bi electroplated films supported by stems that connect the absorber to the detector below. We discuss some of the methods used to produce x-ray absorbers meeting these specifications for ATHENA. To tune the thermal conductance of the device and the effect on the normal-to superconducting transition shape, the stems need to be small diameter and can have a weak bottle-neck connection to the substrate. A funnel shape of the stem using a proximity exposed photoresist mold has been developed to improve the strength of the connections. Further requirements on the absorbers include low levels of fine particulate remaining on the substrate after production and zero shorts between absorbers due to incomplete ion milling or trapped fine particular between absorbers. To optimize for post patterning substrate cleanliness and absorber yield, we have examined several methods of absorber fabrication. Three such methods are 1) an ion mill/wet etch combination, 2) a photoresist mold for electroplating followed by wet or dry etch to remove the seed layer, and 3) an electroplating process with leveling to smooth the surface followed by ion mill to separate the absorbers. The different combinations of wet and dry etches lead to different yields and surface appearance of the absorber sidewalls. We present results on the achieved pixel yields and the energy resolution of pixels made with the various fabrication methods. We discuss the impact of absorber patterning method on performance, uniformity, and yield.

Edward J Wassell↗

Influence of fabrication on microstructure and heat affected zone width in weldments of nuclear reactor pressure vessel steel

Advanced manufacturing routes such as electron beam welding and powder metallurgy with hot isostatic pressing are increasingly used across energy and aerospace industries, where the reliable prediction of weld behavior and heat affected zone (HAZ) evolution is critical. This study examines how fabrication routes and post-weld heat treatments influence phase distribution, crystallite size, microstrain, and dislocation density in nuclear reactor pressure vessel steels using synchrotron X-ray diffraction (SXRD). Retained austenite occurs only in samples that did not undergo austenitization, whereas an austenitizing heat treatment fully eliminates retained austenite and produces a more uniform microstructure across the weldment in terms of phase fraction, dislocation density, and microstrain. The Rosenthal solution underestimates the HAZ width for powder metallurgy samples. A newly proposed modified Rosenthal solution, reducing density by accounting for porosity, matches the SXRD-measured HAZ width with a 0.65% error. Structure–property correlations reveal that dislocation density correlates strongly with nanohardness in homogenous microstructures, while in heterogenous weldments nanohardness is further influenced by the presence of dissimilar phase boundaries. These findings provide new insight into the thermal and microstructural response of powder metallurgy fabricated steels and offer a framework for optimizing welding procedures and heat treatments in advanced manufacturing applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Final Techno-Economic Analysis of 550 MWe Supercritical PC Power Plant CO 2 Capture with Linde-BASF Advanced PCC Technology

This topical report presents the techno-economic evaluation of a 550 MWe supercritical pulverized coal (PC) power plant utilizing Illinois No. 6 coal as fuel, integrated with 1) a previously presented (for a subcritical PC plant) Linde-BASF post-combustion CO 2 capture (PCC) plant incorporating BASF’s OASE® blue aqueous amine-based solvent (LB1) [Ref. 6] and 2) a new Linde-BASF PCC plant incorporating the same BASF OASE® blue solvent that features an advanced stripper interstage heater design (SIH) to optimize heat recovery in the PCC process. The process simulation and modeling for this report is performed using Aspen Plus V8.8. Technical information from the PCC plant is determined using BASF’s proprietary thermodynamic and process simulation models. The simulations developed and resulting cost estimates are first validated by reproducing the results of DOE/NETL Case 12 representing a 550 MWe supercritical PC-fired power plant with PCC incorporating a monoethanolamine (MEA) solvent as used in the DOE/NETL Case 12 reference [Ref. 2]. The results of the techno-economic assessment are shown comparing two specific options utilizing the BASF OASE® blue solvent technology (LB1 and SIH) to the DOE/NETL Case 12 reference. The results are shown comparing the energy demand for PCC, the incremental fuel requirement, and the net higher heating value (HHV) efficiency of the PC power plant integrated with the PCC plant. A comparison of the capital costs for each PCC plant configuration corresponding to a net 550 MWe power generation is also presented. Lastly, a cost of electricity (COE) and cost of CO 2 captured assessment is shown illustrating the substantial cost reductions achieved with the Linde-BASF PCC plant utilizing the advanced SIH configuration in combination with BASF’s OASE® blue solvent technology as compared to the DOE/NETL Case 12 reference. The key factors contributing to the reduction of COE and the cost of CO 2 captured, along with quantification of the magnitude of the reductions achieved by each of these factors, are also discussed. Additionally, a high-level techno-economic analysis of one more highly advanced Linde-BASF PCC configuration case (LB1-CREB) is also presented to demonstrate the significant impact of innovative PCC plant process design improvements on further reducing COE and cost of CO 2 captured for overall plant cost and performance comparison purposes. Overall, the net efficiency of the integrated 550 MWe supercritical PC power plant with CO 2 capture is increased from 28.4% with the DOE/NETL Case 12 reference to 30.9% with the Linde-BASF PCC plant previously presented utilizing the BASF OASE® blue solvent [Ref. 6], and is further increased to 31.4% using Linde-BASF PCC plant with BASF OASE® blue solvent and an advanced SIH configuration. The Linde-BASF PCC plant incorporating the BASF OASE® blue solvent also results in significantly lower overall capital costs, thereby reducing the COE and cost of CO 2 captured from $147.25/MWh and $56.49/MT CO 2 , respectively, for the reference DOE/NETL Case 12 plant, to $128.49/MWh and $41.85/MT CO 2 for process case LB1, respectively, and $126.65/MWh and $40.66/MT CO 2 for process case SIH, respectively. With additional innovative Linde-BASF PCC process configuration improvements, the COE and cost of CO2 captured can be further reduced to $125.51/MWh and $39.90/MT CO 2 for LB1-CREB. Most notably, the Linde-BASF process options presented here have already demonstrated the potential to lower the cost of CO2 captured below the DOE target of $40/MT CO 2 at the 550 MWe scale for second generation PCC technologies.

20 FOSSIL-FUELED POWER PLANTS↗

Calibration of the E3SM Land Model Using Surrogate‐Based Global Optimization

Abstract Calibration of the Energy Exascale Earth System Model (E3SM), land model (ELMv0) is challenging because of its model complexity, strong model nonlinearity, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near‐optimal solution within an affordable time. The goal of this study is to calibrate some of the ELMv0 parameters to improve model projection of carbon fluxes. We propose a computationally efficient global optimization procedure using sparse‐grid based surrogates. We first use advanced sparse grid (SG) interpolation to construct a surrogate system of the ELMv0, and then calibrate the surrogate model in the optimization process. As the surrogate model is a polynomial whose evaluation is fast, it can be efficiently evaluated a sufficiently large number of times in the optimization, which facilitates the global search. We calibrate eight parameters against five years of net ecosystem exchange, total leaf area index, and latent heat flux data from the U.S. Missouri Ozark flux tower. The calibrated model is then used for predicting the three variables in the following 4 years. The results indicate that an accurate surrogate model can be created for the ELMv0 with a relatively small number of SG points, i.e., a few ELMv0 simulations that can be fully parallel. And, the application of the optimized parameters leads to a better model performance and a higher predictive capability than the default parameter values in the ELMv0.

54 ENVIRONMENTAL SCIENCES↗

Structural evolution and magnetic hardness of (Sm,Zr)(Fe,Co,Ti) 12 alloy particles via reduction-diffusion

The quest for achieving high coercivity in Sm(Fe,Co,Ti) 12 alloys, despite their inherent strong magnetocrystalline anisotropy, has posed significant challenges. Recently, (Sm,Zr)(Fe,Co,Ti) 12 monocrystalline particles have exhibited coercivity μ 0 H c > 1.2 T, showcasing promising prospects and significant potential for both manufacturing and research endeavors. This study delves into the structural evolution of (Sm,Zr)(Fe,Co,Ti) 12 (1:12) alloy particles made via the calciothermic reduction-diffusion synthesis process as influenced by the molar ratios of Ca atoms to O 2- ions (Ca/O), annealing time and annealing temperature. Critical insight that informs conditions to optimize the magnetic response is gained via systematic experimentation and advanced electron microscopy. Complex structural features, including core-shell morphologies and intricate multiphase compositions within individual particles, are unveiled. An optimal Ca/O ratio of 1.30 produces particles with a coercivity up to μ 0 H c = 1.63 T, while higher Ca/O ratios induce the formation of a Sm-rich TbCu 7 -type (1: 7 ) phase, which only partially transforms into the desired 1:12 phase during annealing. Persistent remnants of the 1:7 phase locally impact atomic structure, particle morphology, and coercivity. Furthermore, these findings underscore the complex interplay between synthesis parameters, resulting structures, and magnetic properties, informing the design and optimization of high-performance permanent magnets comprised of the (1:12) compound.

36 MATERIALS SCIENCE↗

Machine learning-driven predictive resource management in complex science workflows

Here, the collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource requirements is crucial for each step to allocate optimal resources for effective processing. Estimating resource requirements in advance is challenging due to a wide range of analysis scenarios, varying skill levels among community members, and the continuously increasing spectrum of computing options. One practical approach to mitigate these challenges involves initially processing a subset of each step to measure precise resource utilization from actual processing profiles before completing the entire step. While this two-staged approach enables processing on optimal resources for most of the workflow, it has drawbacks such as initial inaccuracies leading to potential failures and suboptimal resource usage, along with overhead from waiting for initial processing completion, which is critical for fast-turnaround analyses. In this context, our study introduces a novel pipeline of machine learning models within a comprehensive workflow management system, the Production and Distributed Analysis (PanDA) system. These models employ advanced machine learning techniques to predict key resource requirements, overcoming challenges posed by limited upfront knowledge of characteristics at each step. Accurate forecasts of resource requirements enable informed and proactive decision-making in workflow management, enhancing the efficiency of handling diverse, complex workflows across heterogeneous resources.

97 MATHEMATICS AND COMPUTING↗

Advanced manufacturing of 3D custom boron-carbide collimators designed for complex environments for neutron scattering

Scattered-beam collimation is a very useful method to reduce unwanted backgrounds and to boost the desired sample signal instead. This approach is of particular interest for samples contained within a complex environment that gives rise to much unwanted parasitic scatter. As neutron scattering instrument and techniques advances, small samples are becoming of more and more interest, which necessitates optimized collimation. Here, in this work, we describe a concept for the design and fabrication of advanced scattered-beam collimation 3D printed from B 4 C specifically tailored for samples contained within a complex environment. This concept is demonstrated through the use of a diamond anvil cell for high pressure experimentation, a technique that very typically requires small samples. The collimators here are designed through a modeling procedure via Monte Carlo neutron ray tracing that encompasses the entire system: the instrument, the complex environment and the collimator. Since the first approach of simply scaling up of the print-size was not successful, a novel concept of a multi-part alternate-blade collimator was developed. This approach addresses printing constraints but gives greater flexibility in design. Its performance is computationally compared against an unprintable progressively tighter blade collimator to assess the effect of alternating blades. No strong difference was observed. Its performance was validated through experimentation at the Spallation Neutron Source. The results emphasize the critical importance of ultra-high precision alignment while showing good overall agreement between simulation and experiment and underscore the feasibility of the method and its real-world application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Current Status of Clinical Trials for Cervical and Uterine Cancer Using Immunotherapy Combined With Radiation

Novel therapies combined with radiation continue to be of significant interest in the developmental treatment paradigm of gynecologic cancers. Clinical implementation of immunotherapy in oncology has rapidly changed the treatment landscape, options, paradigm, and outcomes through clinical trials. Immunotherapy has emerged as a therapeutic pillar in the treatment of solid tumors with demonstrable synergistic activity when combined with radiation therapy and chemoradiotherapy by an alteration or enhancement of the immune system. In solid tumors, radiation therapy induces migration of dendritic cells, T cell activation, and proliferation, and increases in tumor-infiltrating lymphocytes. These immunomodulatory effects in conjunction with immune checkpoint blockade are currently under active investigation in the adjuvant, definitive, and metastatic settings. Results from early phase trials demonstrate promising efficacy and overall tolerable toxicity profiles of combined modality treatment. There is significant interest in optimizing the treatment for patients with locally advanced cervical cancer beyond the standard of care—chemoradiation—which has been in place for the last 30 years. The majority of cervical cancer emerges after persistent infection with a high-risk subtype of the human papillomavirus, where viral oncoproteins lead to cellular changes and immortalization. As a result, immune tolerance can develop, resulting in cancer. Knowledge of the mechanism of human papillomavirus–related oncogenesis suggests that immune therapy or checkpoint blockade can reinvigorate an antitumor immune response. Current clinical trials are exploring the therapeutic potential of these approaches. Uterine cancers have been grouped into 4 molecular subclasses by their driver mutations, mutational burden, and copy-number alterations. Of these subgroups, the polymerase epsilon–mutated and microsatellite-unstable may represent up to 40% of endometrial cancers, and they have been shown to be immunogenic. Because of the inherent immunogenicity of these MSI-high tumors, combined immune modulation strategies, including chemotherapy, radiation, and immunotherapy and immune checkpoint inhibitor therapy, are being explored to improve treatment outcomes. In this review, we explore current immunomodulatory and multimodality therapeutic approaches in the treatment of cervical and uterine cancer through ongoing clinical trials investigating the combination of immunotherapy and radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

Peters-Lidard, Christa D.↗