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At least 217 records · Page 12

WaterTAP 0.4 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.5 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.6 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.7 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.8 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.10 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.11 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.12 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 1.0 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

AS↗

Numerical experiments on the role of radiative processes in the development and maintenance of upper level clouds

A time-dependent, two-dimensional Eulerian model is presented whose purpose is to obtain more realistic parameterizations of extended high level cloudiness, and the results of a numerical experiment using the model are reported. The model is anelastic and the Bousinesque assumption is invoked. Unresolved subgrid scale processes are parameterized as eddy diffusion processes. Two phases of water are incorporated and equilibrium between them is assumed. The effects of infrared radiative processes are parametrically represented. Two simulations were conducted with identical initial conditions; in one of them, the radiation term was never turned on. The mean values of perturbation potential temperature at each level in the domain are plotted versus height after 15, 30, and 60 minutes of simulated time. The influence of the radiative term is seen to impose a cooling trend, leading to an increased generation of ice water and an increased generation of turbulent kinetic energy in the cloud layer.

Starr, D. O'C.↗

Bench-Scale Development of Promoted High-Capacity Structured Sorbents (Final Technical Report)

The project objective was to develop high-capacity structured sorbent capable of achieving low CO 2 removal from air. The sorbent framework consists of an amine-functionalized onto hydrophobic polymer backbone with an added promoter. The functionalized amine provides high CO 2 capacity and adsorption rates and the polymer backbone to reduce water uptake. For the sorbent development, multiple functionalized amines and promoters were assessed to select a candidate that achieved high CO 2 capacity, high adsorption rate, and high stability. A sorbent-coated filter design was selected as the structured sorbent, which provides high sorbent loading capacity and contains an electrically conductive nonwoven filter substrate that can be Joule-heated to provide efficient utilization of available electricity for sorbent regeneration. A commercial partner operated a pilot filter manufacturing line to produce the filter panels coated with the developed sorbent. A 1 kg CO 2 /day bench unit was designed and fabricated to test the structured filter sorbent. The key achievements from the structured sorbent development activity were demonstrating that existing filter industrial-scale processes can be used for manufacturing Susteon’s structured sorbent and completing a proof-of-concept demonstration of the commercially manufactured structured sorbent filters for CO 2 capture from air with direct, Joule-heated regeneration. A techno-economic assessment with sensitivity analysis was conducted on a 100,000 TPY facility with 85% operating capacity. Through sorbent optimization and process design improvements, it is estimated that the cost of capture was reduced from $\$$349/tCO 2 to $\$$241/tCO 2 . The TEA projects further reductions to $165/tCO 2 through enhancements in CO 2 adsorption rate and sorbent capacity and reducing manufacturing and scale up risks. A life cycle analysis was conducted on the same 100,000 TPY facility and confirmed that the facility’s electricity demand drives its greenhouse gas impact. It was determined that electricity supplied through the current grid mix would result in net-positive CO 2 emissions and that achieving net-negative emissions is only possible by powering the system with renewable electricity or fossil fuel sources equipped with carbon capture and sequestration.

36 MATERIALS SCIENCE↗

Cosmic rays in the heliosphere - Present status and future opportunities

The general theory of charged-particle transport and acceleration is reviewed and application to the heliosphere discussed in detail. The present status of understanding is briefly surveyed, with emphasis on large-scale processes. Opportunities for increasing understanding through the confrontation of theory, modeling and observations are outlined. It is concluded that the largest advances in this understanding in the next few years will come from coordinated theoretical and observations studies of large-scale phenomena requiring energetic-particle, magnetic-field, and plasma data from several spacecraft. Fundamental studies of the interactions between cosmic rays and turbulent plasma to study transport coefficients, details of interactions with shocks, etc, are also important in the longer term.

Jokipii, J. R.↗

Arctic Research NASA's Cryospheric Sciences Program

Much of NASA's Arctic Research is run through its Cryospheric Sciences Program. Arctic research efforts to date have focused primarily on investigations of the mass balance of the largest Arctic land-ice masses and the mechanisms that control it, interactions among sea ice, polar oceans, and the polar atmosphere, atmospheric processes in the polar regions, energy exchanges in the Arctic. All of these efforts have been focused on characterizing, understanding, and predicting, changes in the Arctic. NASA's unique vantage from space provides an important perspective for the study of these large scale processes, while detailed process information is obtained through targeted in situ field and airborne campaigns and models. An overview of NASA investigations in the Arctic will be presented demonstrating how the synthesis of space-based technology, and these complementary components have advanced our understanding of physical processes in the Arctic.

Waleed, Abdalati↗

The Complexity of the Day-Side X-Line During Southward Interplanetary Magnetic Field

High-resolution global magnetohydrodynamics (MHD) simulations include both meso- and global-scale processes occurring at the magnetopause, which interact to determine the time-dependent orientation of the day-side x-line (DXL). This study demonstrates that the global orientation of the DXL in GAMERA global MHD simulations varies on a time scale of minutes during steady southward interplanetary magnetic field conditions. This behavior manifests in observational data when reconnection outflows indicate that the direction to the x-line is opposite to the prediction from a steady-state model of the reconnection location. Because steady-state models of the DXL do not capture dynamics that are independent of solar wind variations, particularly surface waves and flux transfer events, they represent a time-averaged state of the system.

Brandon Burkholder↗

Altimeter Observations of Baroclinic Oceanic Inertia-Gravity Wave Turbulence

For a wide range of nonlinear wave processes - from capillary to planetary waves - theory predicts the existence of Kolmogorov-type spectral cascades of energy and other conserved quantities occuring via nonlinear resonant wave-wave interactions. So far, observations of wave turbulence (WT) have been limited to small-scale processes such as surface gravity and capillary-gravity waves.

wave processees capillary waves planetary waves Ko↗

The SENSEI Generic In Situ Interface: Tool and Processing Portability at Scale [Book Chapter]

One key challenge when doing in situ processing is the investment required to add code to numerical simulations needed to take advantage of in situ processing. Such instrumentation code is often specialized, and tailored to a specific in situ method or infrastructure. Then, if a simulation wants to use other in situ tools, each of which has its own bespoke API [4], then the simulation code team will quickly become overwhelmed with having a different set of instrumentation APIs, one per in situ tool or method. In an ideal situation, such instrumentation need happen only once, and then the instrumentation API provides access to a large diversity of tools. In this way, a data producer’s instrumentation need not be modified if the user desires to take advantage of a different set of in situ tools. The SENSEI generic in situ interface addresses this challenge, which means that SENSEI-instrumented codes enjoy the benefit of being able to use a diversity of tools at scale, tools that include Libsim, Catalyst, Ascent, as well as user-defined methods written in C++ or Python. SENSEI has been shown to scale to greater than 1M-way concurrency on HPC platforms, and provides support for a rich and diverse collection of common scientific data models. Furthermore, this chapter presents the key design challenges that enable tool and processing portability at scale, some performance analysis, and example science applications of the methods.

Bethel, E. Wes↗

Interfacial Void Formation and Self-Healing in Oxide Scales on Al-containing High-Entropy Alloy

The exceptional high-temperature oxidation resistance of Al-containing high-entropy alloys (HEAs) is often attributed to the formation of a protective α-Al 2 O 3 scale. However, the dynamic, atomic-scale mechanisms governing the stability of this scale—including interfacial void formation and the often-postulated but rarely visualized “self-healing” capacity—remain poorly understood. Herein, we reveal the complex evolution of the triple-layer oxide scale on an Al 10 CoCrFeNi HEA through combined electron microscopy and diffraction study. We show that interfacial voids are an inherent consequence of the scaling process, originating from two distinct mechanisms: the Kirkendall effect at the interface between the γ-Al 2 O 3 /α-Al 2 O 3 and alloy driven by cationic diffusion imbalance and volumetric contraction due to phase transformations at the spinel/Cr 2 O 3 interface. Crucially, we provide microstructural evidence consistent with an intrinsic self-healing response. This process is driven by coupled inward diffusion of oxygen and outward diffusion of metal cations, leading to the in-situ formation of transient θ-Al 2 O 3 and spinel phases that partially fill and seal the voids. Here, these results provide atomic-scale insights into the phase evolution, defect formation, and self-repair of oxide scales in HEAs—highlighting pathways to enhance their oxidation resistance in extreme environments.

High-entropy alloy↗

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA). Final report

The goal of the Stahl lab is to use a combination of isotopic, genomic, and activity-based analyses in the field, of selected field isolates, and defined synthetic communities to identify sources and sinks of different nitrogen species in the field, focusing on the FRC at the ORNL. The most general research objective is to characterize variants in the pathway for denitrification among field isolates and synthetic microbial assemblies as a foundation for predicting the biotic and abiotic controls of nitrogen and carbon transformations in the field. Specifically, we have focused on characterizing environmental controls of nitrous oxide emissions, an important greenhouse gas and ozone depleting molecule. Studies have mapped the flux of nitrous oxide and controlling genetic elements within the FRC subsurface, indicating the importance of different enzyme variants in nitrous oxide production and consumption in controlling surface emissions. We have developed methods to quantify and catalog the isotopic signatures imparted on nitrous oxide by different nitrous oxide reductase variants in isolated organisms and model synthetic communities. We have developed methods to quantify and catalog the nitrous oxide affinity of field relevant isolates and their biomass yield when respiring nitrous oxide on different carbon substrates. We continue to expand the collection of field-relevant microbial isolates within ENIGMA by focused enrichment and isolation from field material. These objectives have been facilitated by the development of new technologies, including: 1) the development of a multiplexed automated optical density measurement system for quantifying growth kinetics of microorganisms dependent on gaseous substrates in monoculture or gas exchange in synthetic communities and 2) the development of a microcalorimetric analysis format to quantify the impact of environmental stress on microbial maintenance energy. Since field relevant processes are mediated by assemblies of organisms interacting with each other and their local environment, we have also collaborated with other ENIGMA investigators on the assembly and characterization of synthetic communities. These studies have evaluated the role of organisms lacking a complete pathway for denitrification in the control of field processes, measuring process rates of assemblies of organisms that individually lack the full denitrification pathway but mediate the complete denitrification when growing together. These efforts have so far resulted in the publication of 18 peer reviewed papers ranging from ecological and physiological drivers of pathway optimization to field-scale process characterization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗