AOT Data Assimilation Algorithm: Parameter Recovery, Applications, and a Nonlinear Algorithm
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Carlson, Elizabeth Anne↗
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Development of a Flotation Simulator That Can Predict Grade vs. Recovery Curves from Mineral Liberation Data
Flotation is a kinetic process designed to separate mineral fines by control of hydrophobicity. In general, both the recovery and selectivity of a flotation process increase with contact angle. It is difficult, however, to model flotation kinetics using the thermodynamic parameter. In the present work, we consider flotation as heterocoagulation so that the bubble-particle interactions occurring in the pulp phase of a flotation cell can be modeled using the hydrophobic force as a kinetic parameter that can represent the role of contact angles in flotation. Here, the pulp-phase model developed in this manner has been combined with a froth-phase model developed earlier by considering the effect of particles in film thinning kinetics and bubble coarsening (Park et al, 2018). The combined model has been used to develop a flotation simulator that can be used to construct grade vs. recovery curves from feed characteristics (e.g., mineral liberation and particle size) and various operating parameters. The simulator has been tested successfully against a set of bench-scale continuous flotation test results reported in the literature (dos Santos and Galery, 2018).
58 GEOSCIENCES↗
Approximate recoverability and relative entropy II: 2-positive channels of general von Neumann algebras
Abstract We generalize our results in paper I in this series to quantum channels between general von Neumann algebras, proving the approximate recoverability of states which undergo a small change in relative entropy through the channel. To this end, we derive a strengthened form of the quantum data processing inequality for the change in relative entropy of two states under a channel between two von Neumann algebras. Compared to the usual inequality, there is an explicit lower bound involving the fidelity between the original state and a recovery channel.
97 MATHEMATICS AND COMPUTING↗
Comment on Comment on “Anomalous structural recovery in the near glass transition range in a polymer glass: Data revisited in light of temperature variability in vacuum oven‐based experiments”*
Abstract Cangialosi, Alegría, and Colmenero have made a comment on a paper of ours [Polym. Eng. Sci. 2022:1–13], in which we discussed the concern that the enthalpy recovery data reported by Cangialosi and co‐workers [Phys. Rev. Lett. 2013;111(9):095701] for polystyrene aged up to 15 K below glass transition temperature was anomalous and contradicted existing experimental results from the literature over a similar range of aging conditions. Their response shifts the focus away from the raised questions about their experimental results and attempts to invalidate the data that we cited in support of our argument. Here we respond to the comment and add additional analysis that suggests the structural recovery response of glassy materials exhibits smooth behavior over the full range of measurements, up to 7 or 8 logarithmic decades. We do this by referring to the work on the intrinsic isotherm down‐jump and memory responses of poly(vinyl acetate) between 40°C and 15°C over six logarithmic decades by Kovacs [Fortsch. Hochpolym. Fo. 1963;3(1/2):394–508], the small‐strain tensile creep of poly(vinyl chloride) quenched from 90°C to 40°C (approximately 40°C below T g ) over seven logarithmic decades from Struik [Polym Eng. Sci., 1977;17:165–173], and the volume recovery behavior for aging times up to 3 months in a temperature range between 95°C and −50°C by Greiner and Schwarzl [Rheol. Acta. 1984;23(4):378–395]. We also add discussion that an isothermal aging procedure using a vacuum oven is highly vulnerable to temperature errors due to the problem of good temperature control when the heat transfer mechanism is primarily radiative.
Jin, Shuang↗
Investigation of the yielding transition in concentrated colloidal systems via rheo-XPCS
We probe the microstructural yielding dynamics of a concentrated colloidal system by performing creep/recovery tests with simultaneous collection of coherent scattering data via X-ray Photon Correlation Spectroscopy (XPCS). This combination of rheology and scattering allows for time-resolved observations of the microstructural dynamics as yielding occurs, which can be linked back to the applied rheological deformation to form structure–property relations. Under sufficiently small applied creep stresses, examination of the correlation in the flow direction reveals that the scattering response recorrelates with its predeformed state, indicating nearly complete microstructural recovery, and the dynamics of the system under these conditions slows considerably. Conversely, larger creep stresses increase the speed of the dynamics under both applied creep and recovery. The data show a strong connection between the microstructural dynamics and the acquisition of unrecoverable strain. By comparing this relationship to that predicted from homogeneous, affine shearing, we find that the yielding transition in concentrated colloidal systems is highly heterogeneous on the microstructural level.
42 ENGINEERING↗
Temporal dynamics of the multi-omic response to endurance exercise training
Regular exercise promotes whole-body health and prevents disease, but the underlying molecular mechanisms are incompletely understood. Here, the Molecular Transducers of Physical Activity Consortium profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome and immunome in whole blood, plasma and 18 solid tissues in male and female Rattus norvegicus over eight weeks of endurance exercise training. The resulting data compendium encompasses 9,466 assays across 19 tissues, 25 molecular platforms and 4 training time points. Thousands of shared and tissue-specific molecular alterations were identified, with sex differences found in multiple tissues. Temporal multi-omic and multi-tissue analyses revealed expansive biological insights into the adaptive responses to endurance training, including widespread regulation of immune, metabolic, stress response and mitochondrial pathways. Many changes were relevant to human health, including non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health and tissue injury and recovery. The data and analyses presented in this study will serve as valuable resources for understanding and exploring the multi-tissue molecular effects of endurance training and are provided in a public repository (https://motrpac-data.org/).
59 BASIC BIOLOGICAL SCIENCES↗
Warming of the lower Columbia River , 1853 to 2018
Abstract Water temperature is a critical ecological indicator; however, few studies have statistically modeled century‐scale trends in riverine or estuarine water temperature, or their cause. Here, we recover, digitize, and analyze archival temperature measurements from the 1850s onward to investigate how and why water temperatures in the lower Columbia River are changing. To infill data gaps and explore changes, we develop regression models of daily historical Columbia River water temperature using time‐lagged river flow and air temperature as the independent variables. Models were developed for three time periods (mid‐19th, mid‐20th, and early 21st century), using archival and modern measurements (1854–1876; 1938–present). Daily and monthly averaged root‐mean‐square errors overall are 0.89°C and 0.77°C, respectively for the 1938–2018 period. Results suggest that annual averaged water temperature increased by 2.2°C ± 0.2°C since the 1850s, a rate of 1.3°C ± 0.1°C/century. Increased water temperatures are seasonally dependent. An increase of approximately 2.0°C ± 0.2°C/century occurs in the July–Dec time‐frame, while springtime trends are statistically insignificant. Rising temperatures change the probability of exceeding ecologically important thresholds; since the 1850s, the number of days with water temperatures over 20°C increased from ~5 to 60 per year, while the number below 2°C decreased from ~10 to 0 days/per year. Overall, the modern system is warmer, but exhibits less temperature variability. The reservoir system reduces sensitivity to short‐term atmospheric forcing. Statistical experiments within our modeling framework suggest that increased water temperature is driven by warming air temperatures (~29%), altered river flow (~14%), and water resources management (~57%).
54 ENVIRONMENTAL SCIENCES↗
A Dynamically-Reconfigurable Burst-Mode Link Using a Nanosecond Photonic Switch
Fast optical circuit switching has great potential to solve scaling issues with traditional packet-switch based networks and improve bandwidth and power efficiency in datacenter and high-performance computing applications. One difficultly in utilizing a fast optical switch is that the optical signal must be rapidly reacquired after each switching event so as to not significantly impact the overall throughput of the system. In this work we present a system-level integration of a nanosecond-scale $2 \times 2$ silicon photonic switch with a 25-Gbps burst-mode receiver that can lock in 31 ns. A novel FPGA-based control plane was used to generate test data, control the silicon photonic switch and burst-mode receiver, and measure bit errors at 12.5 and 20 Gbps. Error-free links (BER $< 10^{-12}$ ) with system-level reconfiguration times below 60 ns (at 20 Gbps) and 90 ns (at 12.5 Gbps) including bit- and frame-synchronization are demonstrated.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Risk-Aware Measurement Synchronization and Recovery for DSSE With Heterogeneous Data Sources
Power distribution systems are increasingly integrating heterogeneous sensors with varying data reporting rates and types, which pose challenges to achieving observability at the desired temporal resolution of distribution system state estimation (DSSE). Multisensor failures caused by extreme events exacerbate these issues, introducing substantial uncertainties into DSSE. This article proposes a novel solution to these challenges by ensuring high-resolution system observability despite heterogeneous data sources and multisensor failures. First, a deep learning architecture combining long short-term memory (LSTM) and graph convolutional network (GCN) is employed to synchronize meters with different reporting rates, aiming to achieve system observability. A random-walk-model-based approach is introduced to generate pseudo-measurements while properly characterizing their uncertainties under multisensor failures. Finally, a disaster-risk-informed observability metric (RiOM) is defined to quantify the uncertainty associated with state estimation results. The proposed framework offers deeper insights into the system observability on the fly compared with conventional analysis. The effectiveness of the framework is demonstrated on an IEEE standard test case and a large-scale real-world distribution feeder in mid-Minnesota in the U.S.
97 MATHEMATICS AND COMPUTING↗
Data for Process Strategies for Recovery of Sugars, Lipids, and Lignin from Oilcane Bagasse Using Natural Deep Eutectic Solvents (NADES)
Sugarcane is being enhanced as a bioenergy crop by engineering it to accumulate and store lipids along with polymeric sugars in vegetative tissues. However, there is no existing process that allows for processing this new crop to recover both lipid and cellulosic sugars from the oilcane bagasse. Therefore, a comprehensive investigation of two pretreatment methods—natural deep eutectic solvents (NADES) and chemical-free hydrothermal pretreatment (HT) was conducted to judge their suitability for recovering fermentable sugars, lipids, and lignin from bagasse. Two NADES, i.e., choline chloride: lactic acid (ChCl:LA) and betaine: lactic acid (BT:LA) were prepared using a 1:2 M ratio and were evaluated for pretreatment of oilcane bagasse at 10, 20, and 50 % (w/w) solids, followed by enzymatic hydrolysis at 10 % (w/w) solids. Notably, ChCl:LA NADES treatment at 10 % (w/w) solids at 140 °C for 2 h, solubilized 78.8 % of lignin and 80.4 % of hemicellulose and allowed 82.7 % enzymatic conversion of glucans to glucose. In contrast, HT pretreatment removed approximately 87.6 % of the hemicellulose and provided an enzymatic glucose yield of 69.7 %. Furthermore, ChCl:LA operated at 50 % solids loading the enriched lipids 2.6-fold (9.2 wt%) in recovered solids compared to HT (6.4 %) and BT:LA (5.1 %) pretreatment processes. NMR-HSQC and GPC analysis showed that ChCl:LA also cleaved the most lignin β–O–4 linkages and demonstrated lower molecular weight compared to HT. This study demonstrates that NADES pretreatment is an effective green processing method for recovering lipids, sugars, and lignin from bioenergy crops at high solid loading (50 % w/w) within the context of an integrated biorefinery.
Conversion↗
A Robust Event Diagnostics Platform: Integrating Tensor Analytics and Machine Learning into Real-time Grid Monitoring
The objective of this project is to develop a robust event diagnostics (RED) platform by integrating state-of-the-art tensor analytics and machine learning into real-time grid monitoring. The proposed platform can effectively analyze and discover the information hiding within the provided PMU data for effective real-time grid monitoring. The proposed RED platform provides a set of robust diagnostics tools for grid operation and management, including 1) data quality assessment, 2) data completion, 3) event detection, and 4) robust event classification. All the functionalities of the RED platform can help the operator to make informed decisions and respond in a timely manner. The developed RED platform will serve as an innovative advisory tool to reliably identify key events and discover new insights about the events and grid characteristics in the PMU data, and contribute to the efficient, safe, reliable operation and design of the nation’s electric system.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Digital Twin Empowered PV Power Prediction
The accurate prediction of photovoltaic (PV) power generation is significant to ensure the economic and safe operation of power systems. To this end, the paper proposes a new digital twin (DT) empowered PV power prediction framework that is capable of ensuring reliable data transmission and employing the DT to achieve high accuracy of power prediction. With this framework, considering potential data contamination in the collected PV data, a generative adversarial network is employed to restore the historical data set, which offers a prerequisite to ensure accurate mapping from the physical space to the digital space. Further, a new DT empowered PV power prediction method is proposed. Therein, we model a DT that encompasses a digital physical model for reflecting the physical operation mechanism and a neural network model (i.e., a parallel network of convolution and bidirectional long-short-term memory model) for capturing the hidden spatial-temporal features. The proposed method enables the use of the DT to take advantages of the digital physical model and the neural network model, resulting in enhanced prediction accuracy. Finally, a real data set is conducted to access the effectiveness of the proposed method.
14 SOLAR ENERGY↗
Warming of the Willamette River, 1850–present: the effects of climate change and river system alterations
Abstract. Using archival research methods, we recovered and combined data from multiple sources to produce a unique, 140-year record of daily water temperature (Tw) in the lower Willamette River, Oregon (1881–1890, 1941–present). Additional daily weather and river flow records from the 1850s onwards are used to develop and validate a statistical regression model of Tw for 1850–2020. The model simulates the time-lagged response of Tw to air temperature and river flow and is calibrated for three distinct time periods: the late 19th, mid-20th, and early 21st centuries. Results show that Tw has trended upwards at 1.1 ∘C per century since the mid-19th century, with the largest shift in January and February (1.3 ∘C per century) and the smallest in May and June (∼ 0.8 ∘C per century). The duration that the river exceeds the ecologically important threshold of 20 ∘C has increased by about 20 d since the 1800s, to about 60 d yr−1. Moreover, cold-water days below 2 ∘C have virtually disappeared, and the river no longer freezes. Since 1900, changes are primarily correlated with increases in air temperature (Tw increase of 0.81 ± 0.25 ∘C) but also occur due to alterations in the river system such as depth increases from reservoirs (0.34 ± 0.12 ∘C). Managed release of water affects Tw seasonally, with an average reduction of up to 0.56 ∘C estimated for September. River system changes have decreased variability (σ) in daily minimum Tw by 0.44 ∘C, increased thermal memory, reduced interannual variability, and reduced the response to short-term meteorological forcing (e.g., heat waves). These changes fundamentally alter the response of Tw to climate change, posing additional stressors on fauna.
54 ENVIRONMENTAL SCIENCES↗
Combining field and remote sensing data to estimate forest canopy damage and recovery following tropical cyclones across tropical regions
Abstract As tropical forests cycle the most water and carbon, it is crucial to understand the short- and long-term effects of intensifying cyclones on these ecosystems. Soil nutrient status has been shown to moderate forest cyclone responses using field litterfall measurements, but litterfall is one of the multiple cyclone impact metrtics, which may or may not be correlated with one another or with site nutrients. We used remotely sensed vegetation indices to quantify immediate damage and two-year recovery for 42 cases across nine tropical forests in Hawaii, Puerto Rico, Mexico, Australia, and Taiwan affected by 12 cyclones between 2004 and 2017. We tested whether changes in leaf area index (LAI) and enhanced vegetation index (EVI) correlated with changes in litterfall observations and how changes varied with total soil phosphorus (P) concentrations across regions. We compared cyclone-induced changes and recovery of LAI and EVI to litterfall observations compiled in a pantropical meta-analysis. We found large variation in changes in LAI and EVI across forests, with the greatest reductions in LAI (−77%) and EVI (−77%) in Mexico (Jalisco) and Puerto Rico, respectively. LAI ( r = −0.52) and EVI ( r = −0.60) changes correlated with those in litterfall across cases. Post-cyclone data showed recovery of LAI by four months, EVI by two months, and litterfall by ten months. We detected larger changes in LAI and EVI in forests with higher soil P, but these relationships were not significant when accounting for cyclone and site as random effects. Principal component analyses indicated a regional clustering of cases related to their contrasting cyclone regimes, with the frequency and intensity of cyclone events negatively correlated. Overall, remote sensing observations complement but do not substitute for ground observations that reveal cyclone damage and post-cyclone recovery in tropical forests, and soil phosphorus moderates some but not all metrics of stability in response to cyclones.
Bloom, Dellena E. (ORCID:0000000205981747)↗
Surrogate modeling of the leaching process in a rare earth elements recovery plant
The data are summarized in the slides for a poster as presented at the 2024 AIChE annual meeting in San Diego, California, USA. The slides summarize our work on the PrOMMiS project over the past year. The slides describe the systematic design and optimization of a flowsheet for the recovery of critical minerals and rare earth elements. Then, it summarizes the results of our benchmarking of surrogate modeling methodologies for the optimization of these flowsheets.
Fardis, Dimitrios↗
Dissolved gas recovery from water using a sidestream hollow-fiber membrane module: First principles model synthesis and steady-state validation
This paper presents a first-principles model for the recovery of dissolved gases from liquids using a sidestream hollow-fiber membrane module. The model avoids the use of new empirical coefficients, thus providing a parametric understanding of the process behavior for future design and optimization of membrane modules. This type of first-principles model could be particularly useful when gas recovery is beneficial to biological or chemical reactions of interest, such as the acetogenesis reactions in two-stage anaerobic digesters. The steady-state behavior of the model was validated against both new experimental data for the recovery of H 2 , CH 4 and H 2 –CH 4 mixtures from pure water, as well as existing published data. The modeled gas recovery predictions agreed with experimental data to an absolute average error of 13%, and an average R value of 0.98. Parametric analysis of mixed-gas recovery suggests possible key transition points in the composition of the recovered gases. For example, at 40 °C, increasing trans-membrane pressure while keeping hydraulic residence time (HRT) under 0.5 s will result in an increase in the ratio of H 2 to CH 4 recovered. Otherwise, increasing trans-membrane pressure will instead decrease the ratio of H 2 to CH 4 recovered. The model has potential to be extended to transient analysis, but has yet to be validated with transient experimental data. Furthermore, this model was successfully implemented in both Python and MATLAB, and provides valuable insights for future net-energy optimization for anaerobic digestion systems with in-situ gas recovery.
Anaerobic Digestion↗
Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities
Improvements in process monitoring and control at water resource recovery facilities (WRRFs) could result in reductions in electricity consumption, chemical inputs, and greenhouse gas emissions, as well as improved energy recovery. Many current WRRF data collection, monitoring, and control approaches use 20th century process monitoring and control systems, which require large design safety factors to ensure reliability in the absence of more advanced, precise controls. Implementation of more modern data-driven control tools could lead to more efficient operations that provide intrinsic reliability with better overall process performance at full-scale. This presentation provides an overview of a recently initiated project "Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities" which will (1) develop and demonstrate data-driven process controls at full-scale facilities for five promising WRRF Applications (i.e., process technologies) that provide whole-plant approaches and offer substantial energy and resource recovery benefits, and (2) create a toolbox of new process control approaches and an implementation guide including five examples for application at utilities. The presentation also provides a detailed overview of the research approach and progress being made on one of the five Applications, namely Application 2: Biological Nutrient Removal (BNR): ammonium-based aeration control (ABAC) / ammonia vs. NOx (AvN) + partial denitration with anammox (PdNA), which is being implemented at Hampton Roads Sanitation District. This project is a collaboration of work being conducted by DC Water, Hampton Roads Sanitation District, Metro Water Recovery, University of Michigan, Northwestern University, US Military Academy - West Point, Black & Veatch, and Oak Ridge National Laboratory. Research partner: U.S. Department of Energy.
54 ENVIRONMENTAL SCIENCES↗
The kinetics of static recovery by dislocation climb
Abstract The initial microstructure of a wide range of structural materials is conditioned by thermo-mechanical treatments such as hot-working, tempering, or solution annealing. At the elevated temperatures associated with these treatments the dislocation microstructure evolves, usually decreasing in density through a process known as static recovery. Despite its technological relevance, static recovery is not fully characterized from a theoretical standpoint, with even the controlling mechanisms subject to debate. In this study, a climb-enabled discrete dislocation dynamics (DDD) capability is leveraged to explore the kinetics of static recovery in pure Fe when controlled by dislocation climb. Quantitative data from these simulations is used to develop a revised static recovery law, and provides the parameters appropriate for predictive microstructure models in Fe. This law differs from previous analytical derivations invoking climb of dislocations, following the logarithmic trends typical of experimental observations where prior work did not. Direct comparison between the recovery law derived from DDD to experimental recovery data in alpha Fe shows strong agreement across a range of temperatures, and suggests that climb is the controlling mechanism for static recovery in pure metals.
36 MATERIALS SCIENCE↗