RSS 1.0Academic Divisions
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Biological and Environmental Science & Engineering (BESE)
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Computer, Electrical and Mathematical Science & Engineering (CEMSE)
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Physical Science & Engineering (PSE)
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Recent Submissions
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Bone-Marrow-Derived Mesenchymal Stem Cells, Their Conditioned Media, Protect against Cyclophosphamide-Induced Infertility in Rats(Frontiers in Pharmacology, Frontiers Media, 2023-03-22) [Article]Cancer is a deadly disease characterized by abnormal cell proliferation. Chemotherapy is one tech-nique of cancer treatment. Cyclophosphamide (CYP) is the most powerful chemotherapy medication, yet it has serious adverse effects. It is an antimitotic medicine that regulates cell proliferation and primarily targets quickly dividing cells, and it has been related to varying levels of infertility in hu-mans. In the current study, we assessed the biochemical, histological, and microscopic evaluations of testicular damage following CYP administration. Further, we have explored the potential protective impact of mesenchymal stem cell (MSCs) transplantation. The biochemical results revealed that ad-ministration of CYP increased serum concentrations of follicle-stimulating hormone (FSH) and lu-teinizing hormone (LH), while it decreased serum concentrations of free testosterone hormone (TH), testicular FSH, LH, and free TH concentrations, testicular total antioxidant capacity (TAC), and testicular activity of superoxide dismutase (SOD) enzyme. The histology and sperm examinations revealed that CYP induced destruction to the architectures of several tissues in the testes, which drastically reduced the Johnsen score as well as the spermatogenesis process. Surprisingly, trans-plantation of MSCs after CYP administration altered the deterioration effect of CYP injury on the testicular tissues, as demonstrated by biochemical and histological analysis. Our results indicated alleviation of serum and testicular sex hormones, as well as testicular oxidative stress markers (TAC and SOD activity), and nearly restored the normal appearance of the testicular tissues, Johnsen score, and spermatogenesis process. In conclusion, our work emphasizes the protective pharmacological use of MSCs to mitigate the effects of CYP on testicular tissues that impair the spermatogenesis process following chemotherapy. These findings indicate that transferring MSCs to chemotherapy patients could significantly improve spermatogenesis
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Parameter Inversion in Geothermal Reservoir Using Markov Chain Monte Carlo and Deep Learning(SPE, 2023-03-21) [Conference Paper]Traditional history-matching process suffers from non-uniqueness solutions, subsurface uncertainties, and high computational cost. This work proposes a robust history-matching workflow utilizing the Bayesian Markov Chain Monte Carlo (MCMC) and Bidirectional Long-Short Term Memory (BiLSTM) network to perform history matching under uncertainties for geothermal resource development efficiently. There are mainly four steps. Step 1: Identifying uncertainty parameters. Step 2: The BiLSTM is built to map the nonlinear relationship between the key uncertainty parameters (e.g., injection rates, reservoir temperature, etc.) and time series outputs (temperature of producer). Bayesian optimization is used to automate the tuning process of the hyper-parameters. Step 3: The Bayesian MCMC is performed to inverse the uncertainty parameters. The BiLSTM is served as the forward model to reduce the computational expense. Step 4: If the errors of the predicted response between the high-fidelity model and Bayesian MCMC are high, we need to revisit the accuracy of the BiLSTM and the prior information on the uncertainty parameters. We demonstrate the proposed method using a 3D fractured geothermal reservoir, where the cold water is injected into a geothermal reservoir, and the energy is extracted by producing hot water in a producer. Results show that the proposed Bayesian MCMC and BiLSTM method can successfully inverse the uncertainty parameters with narrow uncertainties by comparing the inversed parameters and the ground truth. We then compare its superiority with models like PCE, Kriging, and SVR, and our method achieves the highest accuracy. We propose a Bayesian MCMC and BiLSTM-based history matching method for uncertainty parameters inversion and demonstrate its accuracy and robustness compared with other models. This approach provides an efficient and practical history-matching method for geothermal extraction with significant uncertainties.
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Physics-Constrained Neural Network (PcNN): Phase Behavior Modeling for Complex Reservoir Fluids(SPE, 2023-03-21) [Conference Paper]The highly nonlinear nature of equation-of-state-based (EOS-based) flash calculations encages high-fidelity compositional simulation, as most of the CPU time is spent on detecting phase stability and calculating equilibrium phase amounts and compositions. With the rapid development of machine learning (ML) techniques, they are growing to substitute classical iterative solvers for speeding up flash calculations. However, conventional data-driven neural networks fail to account for physical constraints, like chemical potential equilibrium (equivalent to fugacity equality in the PT flash formulation) and interphase/intraphase mass conservation. In this work, we propose a physics-constrained neural network (PcNN) that first conserves both fugacity equality and mass balance constraints. To ease the inclusion of fugacity equality, it is reformulated in terms of equilibrium ratios and then introduced with a relaxation parameter such that phase split calculations are extended to the single-phase regime. This makes it technologically feasible to incorporate the fugacity equality constraint into the proposed PcNN model without any computational difficulty. The workflow for the development of the proposed PcNN model includes four steps. Step 1: Perform the constrained Latin hypercube sampling (LHS) to generate representative mixtures covering a variety of fluid types, including wet gas, gas condensate, volatile oil, and black oil. Step 2: Conduct PT flash calculations using the Peng-Robinson (PR) EOS for each fluid mixture. A wide range of reservoir pressures and temperatures are considered, from which we sample the training data for each fluid mixture through grid search. Step 3: Build an optimized PcNN model by including the fugacity equality and mass conservation constraints in the loss function. Bayesian optimization is used to determine the optimal hyperparameters. Step 4: Validate the PcNN model. In this step, we conduct blind validation by comparing it with the iterative PT flash algorithm.
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On Performance of Wireless-Powered FD Relaying Network with Imperfect SIC and Hardware Impairments(IEEE, 2023-03-21) [Conference Paper]In this paper, we analyze the performance of a wireless-powered full-duplex (FD) relaying network over generalized Nakagami-m fading channels for 5G and beyond wireless communication systems. We employ a power beacon that provides a stable and reliable radio-frequency energy and resolves the energy-constraint problem. We also employ a time-switching (TS) receiver for simultaneous energy harvesting and information transmission. We consider the impact of residual self-interference (RSI) because of the imperfect self-interference cancellation. Further, we consider the impact of transceiver hardware impairments (HIs). For the performance analysis, we derive the closed-form expressions of outage probability, system throughput, and energy efficiency over Nakagami-m fading channels. We highlight the impact of RSI, HIs, TS factor, overall system ceiling effect, and other system parameters on the performance of the considered network. An optimal value of the TS factor is obtained for which the considered network exhibits optimum outage performance. In last, we perform the Monte-Carlo simulations to verify the derived closed-form expressions.
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Experimental and Computational Fluid Dynamics Investigation of Mechanisms of Enhanced Oil Recovery via Nanoparticle-Surfactant Solutions(Energy & Fuels, American Chemical Society (ACS), 2023-03-21) [Article]The enhancement in surfactant performance at downhole conditions in the presence of nanomaterials has fascinated researchers’ interest regarding the applications of nanoparticle-surfactant (NPS) fluids as novel enhanced oil recovery (EOR) techniques. However, the governing EOR mechanisms of hydrocarbon recovery using NPS solutions are not yet explicit. Pore-scale visualization experiments clarify the dominant EOR mechanisms of fluid displacement and trapped/residual oil mobilization using NPS solutions. In this study, the influence of multiwalled carbon nanotubes (MWCNTs), silicon dioxide (SiO2), and aluminum oxide (Al2O3) nanoparticles on the EOR properties of a conventional surfactant (sodium dodecyl benzene sulfonate, SDBS) was investigated via experimental and computational fluid dynamics (CFD) simulation approaches. Oil recovery was reduced with increased temperatures and micromodel heterogeneity. Adding nanoparticles to SDBS solutions decreases the fingering and channeling effect and increases the recovery factor. The simulation prediction results agreed with the experimental results, which demonstrated that the lowest amount of oil (37.84%) was retained with the micromodel after MWCNT-SDBS flooding. The oil within the micromodel after Al2O3-SDBS and SiO2-SDBS flooding was 58.48 and 43.42%, respectively. At 80 °C, the breakthrough times for MWCNT-SDBS, Al2O3-SDBS, and SiO2-SDBS displacing fluids were predicted as 32.4, 29.3, and 21 h, respectively, whereas the SDBS flooding and water injections at similar situations were at 12.2 and 6.9 h, respectively. The higher oil recovery and breakthrough time with MWCNTs could be attributed to their cylindrical shape, promoting the MWCNT-SDBS orientation at the liquid–liquid and solid–liquid interfaces to reduce the oil–water interfacial tension and contact angles significantly. The study highlights the prevailing EOR mechanisms of NPS.
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AB-Gen: Antibody Library Design with Generative Pre-trained Transformer and Deep Reinforcement Learning(Cold Spring Harbor Laboratory, 2023-03-21) [Preprint]Antibody leads must fulfill multiple desirable properties to be clinical candidates. Primarily due to the low throughput in the experimental procedure, the need for such multi-property optimization causes the bottleneck in preclinical antibody discovery and development, because addressing one issue usually causes another. We developed a reinforcement learning (RL) method, named AB-Gen, for antibody library design using a generative pre-trained Transformer (GPT) as the policy network of the RL agent. We showed that this model can learn the antibody space of heavy chain complementarity determining region 3 (CDRH3) and generate sequences with similar property distributions. Besides, when using HER2 as the target, the agent model of AB-Gen was able to generate novel CDRH3 sequences that fulfill multi-property constraints. 509 generated sequences were able to pass all property filters and three highly conserved residues were identified. The importance of these residues was further demonstrated by molecular dynamics simulations, which consolidated that the agent model was capable of grasping important information in this complex optimization task. Overall, the AB-Gen method is able to design novel antibody sequences with an improved success rate than the traditional propose-then-filter approach. It has the potential to be used in practical antibody design, thus empowering the antibody discovery and development process.
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Observation of cnoidal wave localization in nonlinear topolectric circuits(Physical Review Research, American Physical Society (APS), 2023-03-21) [Article]We observe a localized cnoidal (LCn) state in an electric circuit network. Its formation derives from the interplay of nonlinearity and the topology inherent to a Su-Schrieffer-Heeger (SSH) chain of inductors. Varicap diodes act as voltage-dependent capacitors, and create a nonlinear on-site potential. For a sinusoidal voltage excitation around midgap frequency, we show that the voltage response in the nonlinear SSH circuit follows the Korteweg-de Vries equation. The topological SSH boundary state, which relates to a midgap impedance peak in the linearized limit is distorted into the LCn state in the nonlinear regime, where the cnoidal eccentricity decreases from edge to bulk.
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SEEING THROUGH THE CO2 PLUME: JOINT INVERSION-SEGMENTATION OF THE SLEIPNER 4D SEISMIC DATASET(arXiv, 2023-03-21) [Preprint]4D seismic inversion is the leading method to quantitatively monitor fluid flow dynamics in the subsurface, with applications ranging from enhanced oil recovery to subsurface CO2 storage. The process of inverting seismic data for reservoir properties is, however, a notoriously ill-posed inverse problem due to the band-limited and noisy nature of seismic data. This comes with additional challenges for 4D applications, given inaccuracies in the repeatability of the time-lapse acquisition surveys. Consequently, adding prior information to the inversion process in the form of properly crafted regularization terms is essential to obtain geologically meaningful subsurface models. Motivated by recent advances in the field of convex optimization, we propose a joint inversion-segmentation algorithm for 4D seismic inversion, which integrates Total-Variation and segmentation priors as a way to counteract the missing frequencies and noise present in 4D seismic data. The proposed inversion framework is applied to a pair of surveys from the open Sleipner 4D Seismic Dataset. Our method presents three main advantages over state-of-the-art least-squares inversion methods: 1. it produces high-resolution baseline and monitor acoustic models, 2. by leveraging similarities between multiple data, it mitigates the non-repeatable noise and better highlights the real time-lapse changes, and 3. it provides a volumetric classification of the acoustic impedance 4D difference model (time-lapse changes) based on user-defined classes, i.e., percentages of speed-up or slow-down in the subsurface. Such advantages may enable more robust stratigraphic/structural and quantitative 4D seismic interpretation and provide more accurate inputs for dynamic reservoir simulations. Alongside presenting our novel inversion method, in this work, we introduce a streamlined data pre-processing sequence for the 4D Sleipner post-stack seismic dataset, which includes time-shift estimation and well-to-seismic tie. Finally, we provide insights into the open-source framework for large-scale optimization that we used to implement the proposed algorithm in an efficient and scalable manner.
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A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics(Nature Communications, Springer Science and Business Media LLC, 2023-03-21) [Article]Spatial transcriptomics technologies are used to profile transcriptomes while preserving spatial information, which enables high-resolution characterization of transcriptional patterns and reconstruction of tissue architecture. Due to the existence of low-resolution spots in recent spatial transcriptomics technologies, uncovering cellular heterogeneity is crucial for disentangling the spatial patterns of cell types, and many related methods have been proposed. Here, we benchmark 18 existing methods resolving a cellular deconvolution task with 50 real-world and simulated datasets by evaluating the accuracy, robustness, and usability of the methods. We compare these methods comprehensively using different metrics, resolutions, spatial transcriptomics technologies, spot numbers, and gene numbers. In terms of performance, CARD, Cell2location, and Tangram are the best methods for conducting the cellular deconvolution task. To refine our comparative results, we provide decision-tree-style guidelines and recommendations for method selection and their additional features, which will help users easily choose the best method for fulfilling their concerns.
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Impact of Evanescence Process on Three-Dimensional Sub-Diffusion based Molecular Communication Channel(IEEE Transactions on NanoBioscience, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-21) [Article]In most of the existing works of molecular communication (MC), the standard diffusion environment is taken into account where the mean square displacement (MSD) of an information molecule (IM) scales linearly with time. On the contrary, this work considers the sub-diffusion motion that appears in crowded and complex (porous or fractal) environments (movement of the particles in the living cells) where the particle’s MSD scales as a fractional order power law in time. Moreover, we examine an additional evanescence process resulting from which the molecules can degrade before hitting the boundary of the receiver (RX). Thus, in this work, we present a 3D MC system with a point transmitter (TX) and the spherical RX with the sub-diffusive behavior of an IM along with its evanescence. Furthermore, an IM’s closed-form expressions for the arrival probability and the first passage time density (FPTD) are emulated in the above context. Additionally, we investigate the performance of MC by using the concentration-based modulation technique in a sub-diffusion channel. Finally, the considered MC channel is exploited in terms of the probability of detection, probability of false alarm, and probability of error for different parameters such as the reaction rate, fractional power, and radius of the RX.
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Tuning anticancer properties and DNA-binding of Pt(ii) complexes via alteration of nitrogen softness/basicity of tridentate ligands(RSC Advances, Royal Society of Chemistry (RSC), 2023-03-21) [Article]Nine tridentate Schiff base ligands of the type (N^N^O) were synthesized from reactions of primary amines {2-picolylamine (Py), N-phenyl-1,2-diaminobenzene (PhN), and N-phenyl-1,2-diaminoethane(EtN)} and salicylaldehyde derivatives {3-ethoxy (OEt), 4-diethylamine (NEt2) and 4-hydroxy (OH)}. Complexes with the general formula Pt(N^N^O)Cl were synthesized by reacting K2PtCl4 with the ligands in DMSO/ethanol mixtures. The ligands and their complexes were characterized by NMR spectroscopy, mass spectrometry and elemental analysis. The DNA-binding behaviours of the platinum(II) complexes were investigated by two techniques, indicating good binding affinities and a two-stage binding process for seven complexes: intercalation followed by switching to a covalent binding mode over time. The other two complexes covalently bond to ct-DNA without intercalation. Theoretical calculations were used to shed light on the electronic and steric factors that lead to the difference in DNA-binding behavior. The reactions of some platinum complexes with guanine were investigated experimentally and theoretically. The binding of the complexes with bovine serum albumin (BSA) indicated a static interaction with higher binding affinities for the ethoxy-containing complexes. The half maximal inhibitory concentration (IC50) values against MCF-7 and HepG2 cell lines suggest that platinum complexes with tridentate ligands of N-phenyl-o-phenylenediamine or pyridyl with 3-ethoxysalicylimine are good chemotherapeutic candidates. Pt-Py-OEt and Pt-PhN-OEt have IC50 values against MCF-7 of 13.27 and 10.97 μM, respectively, compared to 18.36 μM for cisplatin, while they have IC50 values against HepG2 of 6.99 and 10.15 μM, respectively, compared to 19.73 μM for cisplatin. The cell cycle interference behaviour with HepG2 of selected complexes is similar to that of cisplatin, suggesting apoptotic cell death. The current work highlights the impact of the tridentate ligand on the biological properties of platinum complexes.
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3D-Printed disposable nozzles for cost-efficient extrusion-based 3D bioprinting(Materials Science in Additive Manufacturing, AccScience Publishing, 2023-03-21) [Article]3D bioprinting has significantly impacted tissue engineering with its capability to create intricate structures with complex geometries that were difficult to replicate through traditional manufacturing techniques. Extrusion-based 3D bioprinting methods tend to be limited when creating complex structures using bioinks of low viscosity. However, the capacity for creating multi-material structures that have distinct properties could be unlocked through the mixture of two solutions before extrusion. This could be used to generate architectures with varying levels of stiffness and hydrophobicity, which could be utilized for regenerative medicine applications. Moreover, it allows for combining proteins and other biological materials in a single 3D-bioprinted structure. This paper presents a standardized fabrication method of disposable nozzle connectors (DNC) for 3D bioprinting with hydrogel-based materials. This method entails 3D printing connectors with dual inlets and a single outlet to mix the material internally. The connectors are compatible with conventional Luer lock needles, offering an efficient solution for nozzle replacement. IVZK (Ac-Ile-Val-Cha-Lys-NH2) peptide-based hydrogel materials were used as a bioink with the 3D-printed DNCs. Extrusion-based 3D bioprinting was employed to print shapes of varying complexities, demonstrating potential in achieving high print resolution, shape fidelity, and biocompatibility. Post-printing of human neonatal dermal fibroblasts, cell viability, proliferation, and metabolic activity were observed, which demonstrated the effectiveness of the proposed design and process for 3D bioprinting using low-viscosity bioinks.
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Visualization of Surface Charge Carrier Diffusion Lengths in Different Perovskite Crystal Orientations Using 4D Electron Imaging(Advanced Optical Materials, Wiley, 2023-03-20) [Article]Understanding charge carrier dynamics on the surface of materials at the nanometer and femtosecond scales is one of the key elements to optimizing the performance of light-conversion devices, including solar cells. Unfortunately, most of the pump-probe characterization techniques are surface-insensitive and obtain information from the bulk due to the large penetration depth of the pulses. However, ultrafast scanning electron microscopy (USEM) is superior in visualizing carrier dynamics at the surface with high spatial-temporal resolution. Here, the authors successfully used USEM to uncover the tremendous effect of surface orientations and termination on the charge carrier of MAPbI3 perovskite single crystals. Time-resolved secondary electrons snapshots and density functional theory calculations clearly demonstrate that charge carrier diffusion, surface trap density, surface work function, and carrier concentration are strongly facet-dependent. The results display a diffusion length of 22 micrometers within 6.0 nanoseconds along (001) orientation. While (100) facet forms defect states that prevent carrier diffusion and shows an increase in the surface work function leading to dark contrast and fast charge carrier recombination. These findings provide a new key component to optimizing the surface of perovskites, thus paving the way for even more efficient and stable solar-cell devices based on perovskite single crystals.
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UAV Assisted IoT Geo-positioning Solution Employing Low-Cost Bluetooth Enabled Tags(IEEE, 2023-03-20) [Conference Paper]Technology integration has enabled value-added services and quality-of-life enhancement in almost all aspects of modern life. In this paper, we present a UAV and low-cost Bluetooth low energy (BLE) tags-based location search system which enables a cart take-home service for shoppers of a supermarket in a model smart colony. The presented system has quality-of-life enhancement as well as carbon footprint reduction effects and can be integrated with the existing security and/or transport system of the model smart colony. Conducted field trials on location accuracy of the system are also presented, showing that carts left by residents outside the home can be located within 6.58m and carts taken inside homes or buildings can be located within 16.43m.
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The effects of chemical and mechanical interactions on the thermodynamic pressure for mineral solid solutions(Authorea, Inc., 2023-03-20) [Preprint]We use a coupled thermodynamically-consistent framework to model reactive chemo-mechanical responses of solid solutions. Specifically, we focus on chemically active solid solutions that are subject to mechanical effects due to heterogeneous stress distributions. The stress generation process is driven solely by volume changes associated with the chemical processes. We use this model to describe the underlying physics during standard geological processes. Furthermore, simulation results of a three-species solid solution provide insights into the phenomena and verify the interleaving between mechanical and chemical responses in the solid. In particular, we show the evolution of the thermodynamic pressure as the system goes to a steady state.
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Engineering grain boundaries in monolayer molybdenum disulfide for an efficient water/ion separation(Research Square Platform LLC, 2023-03-20) [Preprint]Atomically thin two-dimensional (2D) materials have long been considered as ideal platforms for developing separation membranes. However, it is difficult to generate uniform subnanometer pores over large areas on 2D materials. Herein, we report that the well-defined defect structure of monolayer MoS2, namely, eight-membered ring (8-MR) pores typically formed at the boundaries of two antiparallel grains, can serve as molecular sieves for efficient water/ion separation. The 8-MR pores (4.2 × 2.4 Å) in monolayer MoS2 allow rapid single-file water transport while rejecting various hydrated ions. Further, the density of grain boundaries and, consequently, the density of pores can be tuned by regulating the nucleation density and size of MoS2 grains during the chemical vapor deposition process. The optimized MoS2 membrane exhibited an ultrahigh water/NaCl selectivity of ~6.5 × 104 at a water permeance of 232 mol m−2 h−1 bar−1, outperforming the state-of-the-art desalination membranes. When used for direct hydrogen production from seawater by combining the forward osmosis and electrochemical water splitting processes, the membrane achieved ~40 times the energy conversion efficiency of commercial polymeric membranes. It also exhibited a rapid and selective proton transport behavior desirable for fuel cells and electrolysis. The bottom-up approach of creating precise pore structures on atomically thin films via grain boundary engineering presents a promising route for producing large-area membranes suitable for various applications.
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Resident Population Density-Inspired Deployment of K-tier Aerial Cellular Network(IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-20) [Article]Using Unmanned Aerial Vehicles (UAVs) to enhance network coverage has proven a variety of benefits compared to terrestrial counterparts. One of the commonly used mathematical tools to model the locations of the UAVs is stochastic geometry (SG). However, in the existing studies, both users and UAVs are often modeled as homogeneous point processes. In this paper, we consider an inhomogeneous Poisson point process (PPP)-based model for the locations of the users that captures the degradation in the density of active users as we move away from the town center. In addition, we propose the deployment of aerial vehicles following the same inhomogeneity of the users to maximize the performance. In addition, a multi-tier network model is also considered to make better use of the rich space resources. Then, the analytical expressions of the coverage probability for a typical user and the total coverage probability are derived. Finally, we optimize the coverage probability with limitations of the total number of UAVs and the minimum local coverage probability. Finally we give the optimal UAV distribution parameters when the maximum overall coverage probability is reached.
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Flexible self-powered DUV photodetectors with high responsivity utilizing Ga2O3/NiO heterostructure on buffered Hastelloy substrates(Applied Physics Letters, AIP Publishing, 2023-03-20) [Article]In this research, β-Ga2O3/NiO heterostructures were grown directly on CeO2 buffered Hastelloy flexible substrates. With pulsed laser deposition under high temperatures, as-grown β-Ga2O3 and NiO thin films have a preferred out-of-plane orientation along the ⟨−201⟩ and ➎111➉ directions. This is due to the ideal epitaxial ability of the CeO2 buffer layer, which serves as a perfect template for the epitaxial growth of single-oriented NiO and β-Ga2O3 by creating a constant gradient from CeO2 (2.7 Å along ➎001➉) to NiO (2.9 Å along ➎110➉), and eventually to β-Ga2O3 (3.04 Å along ➎010➉). The Hastelloy substrates endow photodetectors with good deformability and mechanical robustness. Moreover, owing to the type-II band alignment of β-Ga2O3/NiO heterostructures, the photodetectors have a good photocurrent at zero bias under 284 nm of light illumination. In addition, the photocurrent is significantly higher than when using an analogous heterostructure (as described in some previous reports), because the β-Ga2O3 and NiO thin films are crystalized along a single orientation with fewer defects.
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Multimode Free-Vibration Decay Column: Small-Strain Stiffness and Attenuation(Journal of Geotechnical and Geoenvironmental Engineering, American Society of Civil Engineers (ASCE), 2023-03-20) [Article]This study presents a simplified resonant column testing method to obtain small-strain dynamic properties of soils in both torsional and flexural vibrations. The method exploits free vibration decay responses of the system produced by manual excitation while the specimen is subjected to an isotropic effective confining stress produced by a vacuum pressure. This method is readily applicable to standard resonant column and torsional shear devices and triaxial cells by attaching a metal bar with one or two accelerometers for manual excitation, but not using an electromagnetic driving plate. This paper describes the apparatus design, test procedure, system calibration, and data analyses, as well as the test results of dynamic properties of a dry sand, including small-strain elastic moduli and damping ratios obtained from the torsional and flexural modes. The results confirm that the suggested method can capture strain-dependent characteristics up to the strains of ∼10−4 beyond typical elastic threshold strains, although the isotropic effective confining stress is limited to ∼90 kPa. This unique testing method provides remarkably consistent and reliable measurement for the dynamic properties of soils, and it avoids any possible bias from the counterelectromotive force.
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On that most over Skinned of Improper Integrals(The College Mathematics Journal, Informa UK Limited, 2023-03-20) [Article]Continuing a much discussed topic of the various ways a particular improper integral can be evaluated, we give three further ways its generalization can be evaluated. Using techniques typically encountered immediately after the calculus sequence of courses we show how the improper integral can be evaluated using the beta and gamma functions, by first converting it to a double integral, and using a property of the Laplace transform.
