342 research outputs found
Neural Networks for Predicting the Mechanical Behavior of Woven Composites with Limited Data and Physical Insights
No full textDeveloping new composite materials with enhanced properties relied on a long trial-and-error process, requiring extensive mechanical testing and deep knowledge about fundamental phenomena and constituent interactions. While analytical micromechanical models have successfully predicted the effective properties of heterogeneous materials with idealized microstructures, computational methods and increased computing power have made it possible to overcome simplifying assumptions. This allows for considering realistic microstructures with complex behaviors and interactive effects of multiple scales on the effective composite behavior.
Despite these advances, simulations of complex multiscale heterogeneous materials, like woven composites, and the transitions from microscale to macroscale still demand significant computational resources, making their integration into fast, practical user codes a persistent challenge. Data-driven surrogate models based on neural networks address the computationally demanding challenge but often suffer from high data requirements, limited interpretability, and poor extrapolation capabilities.
This dissertation explores the intersection of multiscale material analysis and neural networks, aiming to develop a generalized model that can infer woven composites' meso- and macroscale behavior from general load conditions and micromechanical constitutive properties. Several neural network-based surrogate models are designed to serve as efficient alternatives to conventional homogenization techniques, enabling fast and scalable predictions across scales for both elastic and elasto-plastic conditions.
A key focus of this work is to lower the barriers to applying deep learning in multiscale material modeling. To achieve this, strategies are investigated to reduce the required training data while maintaining high-fidelity representations of time-dependent material behavior. Additionally, efforts are made to embed fundamental material constitutive laws directly into neural network architectures. This approach not only follows computational homogenization for woven composites but also enables extrapolation beyond training data while enhancing the explainability of path-dependent network predictions.
Given the interdisciplinary nature of these contributions, the thesis includes introductions that provide the necessary theoretical background for a deeper understanding of the appended papers
Ein Bild und seine Geschichte
No full textAbedi E. A Picture and Its Story. Du : das Kulturmagazin. 2022;(912):93-97.Hermann Hesse's Siddhartha helped the Iranian mathematician Ehsan Abedi get over a difficult time in his life. During a study and research stay in Switzerland, he dedicated a painting to the author. Today it is part of the collection of the Museum Hermann Hesse.Dem iranischen Mathematiker Ehsan Abedi half Hermann Hesses Siddhartha über eine schwere Zeit in seinem Leben hinweg. Während eines Studien- und Forschungsaufenthalts in der Schweiz widmete er dem Autor ein Bild. Heute ist es Teil der Sammlung des Museums Hermann Hesse
Compiled notes for beloved juniors - series 1
No full textThese notes are kept by the author for more than 12 years. Author had started writing these notes since few weeks after he had completed his final MBBS exam with the intention to share officially with his juniors one day. He previously has shared some of them through social media since 13th May 2009. He decided to share now, he chooses year 202
Author Correction: RNAa-mediated epigenetic attenuation of the cell senescence via locus specific induction of endogenous SIRT1 (Scientific Reports, (2022), 12, 1, (15826), 10.1038/s41598-022-17972-9)
No full text\ua9 The Author(s) 2023.The original version of this Article contained an error in the spelling of the author Ehsan Soleymaninejadian which was incorrectly given as Ehsan Soleimaninejadian. The original Article has been corrected
Adsorption media for the removal of phosphorus in subsurface drainage for Michigan corn fields
No full textPhosphorus is a valuable, non-renewable resource in agriculture promoting crop growth. and is used in the global food chain, mainly as fertilizer. Soluble phosphorus plays a part in the eutrophication in freshwater environments, which impacts tourism, human health, environmental safety, and property values. Phosphorus loss from agricultural land is also a loss of investment that went into keeping it on the soil, and its addition into water bodies can increase costs to manage the affected area(s). This research entails selecting the phosphorus adsorption media best suited for removing phosphorus from subsurface drainage in Michigan farms. Selected adsorption media from the literature includes engineered nanomaterials, biochar, and natural materials. These media were evaluated with typical subsurface drainage phosphorus concentrations using batch adsorption and column experiments to verify if the media worked in this application. Both the steel furnace slag (SFS) and PO4Sponge removed soluble reactive phosphorus from 0.500 to below 0.05 mg/L in column experiments at an empty bed contact time of 5-minutes The SFS was the most cost-effective option based on a case-study and generalized analysis. The most expensive option was the use of PO4Sponge media to remove phosphorus, then regenerating it at the manufacturer.Thesis (M.S.)--Michigan State University. Biosystems Engineering, 2020Includes bibliographical references (pages 154-163
Predicting the effects of weir management on drainage discharge of a controlled drainage system in a changing climate
No full textThe widespread adoption of subsurface drainage in the Midwest United States coupled with fertile land and abundant rainfall has made this region the largest producer of corn and soybean in the nation. Although subsurface drainage helps reduce the waterlogging stress on crops by removing nutrient-enriched water from the field, it could contribute to harmful algal blooms in freshwater ecosystems. Controlled drainage (CD) practices can reduce the drainage volume leaving the field and have a positive effect on nutrient load reduction. Although the efficiency of CD under the present climate has been widely studied, it is essential to evaluate its performance in the future to build resilient agricultural systems. In this study, the efficiency of two CD practices was evaluated in reducing drainage discharge for the future based on the height and timing of the weir management. We used the Root Zone Water Quality Model (RZWQM2) to predict the CD management effects on drainage discharge. To obtain reliable simulation results from the RZWQM2 model, it is important to use measured soil-water characteristic parameters and flow data. We used HYPROP to measure the parameters of the soil water characteristic curve which served as input to the model. Additionally, we developed a stage-discharge equation for an AgriDrain metal-edge sharp-crest 45\u2117\u2bb V-notch weir to accurately estimate the drainage discharge from the field. A reliable estimate of the drainage discharge was necessary to accurately estimate the nutrient loss.The recently developed P module of the RZWQM2, known as RZWQM2-P was used in this study to predict drainage discharge and P loss from a subsurface-drained field with clay loam soil. We used the Nash-Sutcliffe model Efficiency (NSE) and percentage bias (PBIAS) statistics to evaluate model performance. While the model showed "good" and "satisfactory" performance in predicting drainage discharge and total phosphorus (TP) load, respectively, it performed unsatisfactorily in predicting the dissolved reactive phosphorus (DRP) load for both calibration and validation periods. The underperformance of the model in simulating DRP load may be due to the inability of the model to partition fertilizer P into different P pools.We predicted the efficiency of two CD management scenarios (i.e., common and aggressive management) in reducing drainage discharge for future climate using the calibrated RZWQM2 model. The CD management scenarios were performed by maintaining the weir height at a higher (i.e., 15 cm for non-growing season and 40 cm for growing season) or lower (i.e., 30 cm for non-growing season or 50 cm for growing season) level inside a control structure and by altering the timing of the CD management based on the planting and harvesting dates. While both common and aggressive management was efficient in reducing drainage discharge for both historic and future periods, the percent reduction of drainage discharge with aggressive management was about 11% higher than the common management. The projected increase in precipitation and temperature in the future would cause increased drainage discharge during fall and winter. The aggressive management will be able to completely restrict the flow during the non-growing season which would reduce the nutrient loss of the surface water bodies. In the future, farmers should plant early to benefit from the projected increase in spring rainfall and avoid dry summers. In conclusion, it is evident from the results of this study that both common and aggressive CD management will continue to be effective in reducing drainage discharge in a changing climate.Thesis (Ph. D.)--Michigan State University. Biosystems Engineering, 2022Includes bibliographical reference
IMPROVING SATURATED BUFFER SYSTEMS PERFORMANCE WITH A NEW DESIGN APPROACH AND MANAGEMENT GUIDELINES FROM AN EVALUATION OF A FIELD EXPERIMENT
No full textThesis (Ph.D.)--Michigan State University. Biosystems Engineering - Doctor of Philosophy, 2024Subsurface drainage is needed for maintaining good crop yields in poorly drained lands, mitigating water stress, ensuring field trafficability, and timely agronomic operations. However, it can lead to water quality issues by providing faster routes for nutrients to leave the field resulting in more nitrate loading. Saturated buffers (SB) are conservation drainage practices aimed at reducing nitrate loss. By redirecting a portion of the drainage discharge through vegetative buffers, nitrate is mainly removed via denitrification. Yet, reported effectiveness varies, necessitating a consistent design approach. Current literature is limited, primarily focusing on Iowa and Illinois. Therefore, there's a need for broader understanding of the SB hydrology and nitrate loading functionality. Better understanding can aid in proposing design and management guidelines to enhance SB performance.We developed a new SB design approach incorporating site-specific conditions to determine the optimal buffer width. Using process-based modeling, we estimated nitrate load removal iteratively across various buffer widths. Performance comparisons with existing SB design approaches utilized modeling and field data from two Michigan sites. SB parameters (buffer width and distribution pipe length) and field data inputs were used to estimate diverted flow and nitrate load removal for each design. Comparison revealed that designs 2 and 3 were equally effective, yielding higher nitrate load removal (20%) than Design 1. Maximizing diverted flow didn't improve nitrate removal, emphasizing the need to target maximum nitrate load removal directly while considering site-specific characteristics. We developed a DRAINMOD-based decision-support tool for SBs (DBDSTSB), to incorporate the new design approach and facilitate its use. Moreover, we validated its prediction performance of the flow and nitrate load parameters utilizing published evaluation criteria of standard statistical indicators and measured data from two fields in Iowa. The DBDSTSB showed \u201cgood\u201d performance in predicting annual field drainage, diverted flow to buffer, nitrate load in drainage, and nitrate load removal by SB. The DBDSTSB\u2019s predictions of the long-term average annual percentages of diverted flow and nitrate load removal were also reasonable, where their deviations from the corresponding measured values amounted to only 1% and 2%, respectively. We conducted an SB field study to assess the stacked CD+SB system's performance and component contributions in reducing drainage discharge and nitrate loading from tiled agricultural fields. The study, from Jun 2019 to Feb 2024 in Michigan, employed a paired-field approach. The stacked CD+SB system notably reduced drainage discharge and nitrate load of free drainage (FD) by annual averages of 43.1% and 83.4%, respectively. The CD component played a major role in these reductions (44.1% and 82.5%, respectively). Conversely, the SB only slightly contributed to overall nitrate load reduction (0.9%). Mild management of the stoplogs, with depths greater than 50 cm, caused backflow and additional nitrate load from the SB. Conversely, intense management, with depths around 30 cm, limited the backflow volume. In conclusion, DBDSTSB facilitates the new design's use and provides credible quantification of SB performance. This can support nitrate trading programs, promoting SB adoption for enhanced nitrate removal. Stacking SB with CD and employing intense management has the potential to improve nitrate removal performance.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
PROTECTING WATER QUALITY AND INCREASING RESILIENCY OF CROP PRODUCTION WITH CLIMATE-SMART DRAINAGE STRATEGIES
No full textThesis (Ph.D.)--Michigan State University. Biosystems Engineering - Doctor of Philosophy, 2024Accurate phosphorus (P) load estimation in subsurface drainage water is critical for assessing the field-scale efficacy of conservation practices and minimizing the environmental impact of P loss from subsurface-drained fields to freshwater bodies like the Great Lakes. Also, to build a more resilient crop production system in a changing climate, it is crucial to understand how future weather patterns affect subsurface drainage design and whether subirrigation will be needed in the future for crop production. In this study, we used high-frequency P concentration measurements to investigate P transport dynamics and evaluate the effects of water sampling strategies on the uncertainty of P load estimation. We also evaluated the change in the optimum drain spacing from using historical (1994 - 2023) and future (2030 - 2059) weather data and assessed the efficacy of subirrigation to alleviate yield reduction due to drought stress in southeast Michigan, USA.We used the HydroCycle-PO4 instrument to measure total reactive P (TRP) concentration at a high resolution from a subsurface-drained field. Hourly TRP concentration and hourly drainage discharge measurements formed the reference P load dataset. Four hypothetical water sampling strategies were evaluated: (a) time-proportional discrete sampling, (b) time-proportional composite sampling, (c) flow-proportional discrete sampling, and (d) flow-proportional composite sampling. All sampling strategies underestimated TRP load compared with the reference dataset, regardless of whether the underestimation was statistically significant. Total reactive P load underestimation changed from 0.2 to 51% as time-proportional discrete sampling intervals increased from 3 h to 14 d. Total reactive P load underestimation changed from 12 to 43% as the time-proportional compositing scenario increased from 1 to 7 d, each with one aliquot per day. In the case of the flow-proportional discrete sampling scenario, the lowest (0.6%) and the highest (\u20135.1%) uncertainties were observed when 1- and 5-mm flow intervals were used. The relative error based on the results provided by the flow-proportional composite sampling ranged from 0.2% when using a 1-mm flow interval to \u20136.7% when using a 5-mm flow interval. In conclusion, the flow-proportional sampling strategies provided a more accurate estimate of cumulative P load with fewer samples because a greater portion of samples were taken at higher flow rates compared with time-proportional sampling strategies.Results showed that there was a good relationship between TRP concentration and drainage discharge (R-squared = 0.60) such that TRP had a transport-limited chemodynamic pattern, that is TRP concentration tended to increase with an increase in flow during events. A 1% increase in drainage discharge resulted in a 1.36% increase in TRP load, indicating a significant increase in P concentration during high flows. We found that flow events substantially contributed to P loss (89%) because of capturing the rapid increase in P concentration during high flows. The rate of increase in P concentration during the rising limb ranged from 0.02 to 0.66 mg/L per hour. The highest 7.7% of drainage flow transported 75% of the TRP load during the monitoring period. The hysteresis pattern tended to be positive (clockwise) during the study period, indicating that preferential flow was a pathway for TRP loss. Most flow events (30 out of 36) displayed a flushing effect in which P concentration increased with a rise in drainage discharge. In conclusion, high-frequency P sampling showed that management and conservation practices should target flow events to reduce P loss.A total of 27 general circulation models with a moderate greenhouse gas emission scenario (shared socioeconomic pathway 2-4.5) were used for climate projections. Simulations were performed using the DRAINMOD model, and the optimum drain spacing was determined based on the maximum average annual return on investment. Results showed that the projected 30-year average annual precipitation is not expected to change significantly while that of the temperature will increase by 2.5\ub0C in the future. Future optimum drain spacings for depths of 75 cm and 125 cm were found to be 300 cm and 600 cm wider than historical spacings, respectively. On average, there was a 23% decrease in 30-year average annual drainage discharge, attributed to an average 17% increase in evapotranspiration. Drought stress is projected to be the primary cause of yield loss in the future, due to increased temperatures and an average 8% deeper water-table depth. Subirrigation shows high potential in reducing year-to-year crop yield variability in the future (decreasing the coefficient of variation for the yield from 0.26 to 0.06, on average) and increasing yield by up to 31%. In the past, subirrigation initiation was feasible in late June with a weir depth of 70 cm. However, in the future, subirrigation is anticipated to be more advantageous when starting sooner in early to mid-June, coupled with a shallower weir depth ranging from 65 cm to 55 cm. In conclusion, a wider drain spacing, providing reduced drainage intensity, along with subirrigation may be needed in the future to mitigate crop yield loss from drought stress.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Efficient Implementation of Spontaneous Calcium Oscillations in the Central Nervous System on Reconfigurable Digital Boards
No full textThis work was supported by the Deanship of Scientific Research at King Khalid University under Grant RGP.1/243/42. This article was recommended by Associate Editor P. K. Meher. (Corresponding author: Yisu Ge.
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