Skip to main content
eScholarship
Open Access Publications from the University of California

Scholarly Works (22 results)

  • Thesis
  • Peer Reviewed
UC Berkeley Electronic Theses and Dissertations (2018)

The technology of base isolating a structure using laminated rubber bearings to protect the structure and the contents of the structure from earthquake damage has been proven effective. This technology has evolved since it was first discovered in the 1980’s. More buildings have been constructed using this technology to ensure that the contents are well protected during the event of an earthquake and more importantly, the structure can continue to operate after an earthquake. This advantage is particularly important for critical structures such as hospitals and emergency centers, and sensitive structures such as nuclear power plants. The use of high damping rubber isolation system has the advantage over most of other isolation systems mainly due to the presence of moderate damping in the material that could help with displacement control without significantly exciting the higher modes response in the structure. In addition, the simplicity in the installation does not require additional installation for supplementary energy dissipating mechanisms.

High damping rubber has been known for the uniqueness in terms of the dynamic and mechanical properties. In addition, this material is rather complex mainly due to the nonlinearity in the force-displacement relationship and several other dependencies such as strain and temperature. Due to the complexity of the material, the development of the phenomenological model to represent this material often resulted with complicated model, which could potentially make the implementation in structural analyses difficult. In this study, with the aim of simplicity, a phenomenological model for high damping rubber isolator was developed while capturing as many important dynamic properties of the material as possible. The calibration of the high damping rubber isolator model was based on the laboratory test results on double shear test piece with high damping rubber material tested up to 500% shear strain. The final model in this study exhibits the characteristic of nonlinearity of the material due to varying shear strain and the change in dynamic properties such as the effective shear modulus and effective damping ratio with shear strain. The dynamic properties of the developed model were observed to closely follow the distribution of the properties observed through laboratory test results. In addition, the relationship between the energy dissipation and shear strain was found to be close to the actual material.

On the other hand, in dynamics, damping is critical for system responding near the resonance frequency. Damping is also known as a mechanism to reduce peak displacement response as observed from the displacement spectra with different damping values. However, it is often overlooked that too much damping in a system, particularly base isolation system, would excite higher mode response. This adverse effect from damping could lead to the damage of vibration sensitive equipment housed in the structure.

Study on bilinear model was included in this work. The definition and implementation of bilinear model based on the ASCE 7-16 design document were studied and outlined. Three typical design scenarios were established and the associated bilinear models were developed. The dynamic properties of these models were evaluated before dynamic analyses were carried out using the two-degree-of-freedom base isolated system. The effectiveness of each isolator model was evaluated using the roof floor response spectra. The results showed that each design scenario has resulted in highly damped isolation system and as a result, higher mode response was excited.

The work concluded with a comparison of the dynamic analyses results using three isolator models, the high damping rubber isolator model, bilinear model, and a model with linear spring model and linear viscous damper. The bilinear model was developed based on the laboratory test results of double shear test piece with high damping rubber material and in accordance to the procedure outlined in the design document. The dynamic properties of the model were calibrated at 100% shear strain, consistent with the calibration of the high damping rubber isolator model. The responses of the two-degree-of-freedom base isolated model using all isolator models subjected to ground motions with different intensities were compiled for comparison. The results showed that the bilinear model overestimated the damping at shear strain less than the design shear strain while underestimated the damping for shear strains beyond the design shear strain. The linear spring model with linear viscous damper exhibited the opposite trend as the model has constant damping ratio independent of shear strain.

With the proper amount of damping modelled in the isolator model and the stiffening effect, the high damping rubber isolator model has shown to be able to control the peak displacement of the system without significantly exciting the higher mode response of the system. Unlike the nature of the bilinear model, the presence of high amount of damping at the small shear strain range has the potential to excite the higher mode response when the system is subjected to weak ground motions.

A simple three-element high damping rubber isolator model has been developed from this study and the dynamic properties were found to closely follow the distribution of the dynamic properties of the material obtained through laboratory test. More thorough analyses would be carried out to ensure the consistency of the procedure in developing this model based on laboratory test results. One of the elements of this model was based on the mathematical model developed using unfilled rubber. Studies can be carried out to investigate the accuracy of this model when used for high damping rubber isolator model, which is a filled rubber. In addition, the arbitrary model used as one of the energy dissipation mechanisms could be improved to better capture the mechanisms for the material.

    Cover page: The Potential Application of Strain-Induced Stiffening in Base Isolation System
    • Article
    • Peer Reviewed
    UC Irvine Previously Published Works (2014)
    The function of protein relies on their folding to assume the proper structure. Probing the structural variations during the folding process is crucial for understanding the underlying mechanism. We present a combined quantum mechanics/molecular dynamics simulation study that demonstrates how coherent resonant nonlinear ultraviolet spectra can be used to follow the fast folding dynamics of a mini-protein, Trp-cage. Two dimensional ultraviolet signals of the backbone transitions carry rich information of both local (secondary) and global (tertiary) structures. The complexity of signals decreases as the conformational entropy decreases in the course of the folding process. We show that the approximate entropy of the signals provides a quantitative marker of protein folding status, accessible by both theoretical calculations and experiments.
      Cover page: Signatures of the Protein Folding Pathway in Two-Dimensional Ultraviolet Spectroscopy
      • Article
      • Peer Reviewed
      UC Davis Previously Published Works (2023)
      Since its discovery in 2016, the Polerovirus Barley virus G has been reported in at least nine countries and multiple species of monocot plants. All of these reports have used PCR and/or sequencing based assays to identify BVG, however none have investigated the biology of BVG. In this study we detail the generation of the first infectious cDNA clone of BVG from archived RNA, thereby producing a valuable experimental tool and system for studying BVG biology. Using this system we identified two compatible aphid vectors and confirmed the susceptibility of several monocot plants, and the dicotyledonous plant host Nicotiana benthamiana, to BVG.
        Creative Commons 'BY-ND' version 4.0 license
        • Article
        • Peer Reviewed
        UC Irvine Previously Published Works (2014)
        Ultraviolet (UV) spectra of proteins originate from electronic excitations of their backbone chromophore and aromatic side chains and provide a sensitive probe of the secondary structure. Recently developed femtosecond lasers allow multidimensional spectroscopy to be extended into the UV regime. Two-dimensional UV (2DUV) techniques, with short pulses, provide a promising tool to study the structures and dynamics of proteins. We combined 2DUV spectroscopy and molecular dynamics generated free energy profiles to simulate the protein electronic transitions and UV photon echo signals to monitor the protein folding process of the small protein Beta3s. Near-ultraviolet (NUV) and far-ultraviolet (FUV) signals illustrate the variation of the 2D correlation plots when the protein evolves along the underlying free energy landscape. Chiral polarization configurations of the NUV and FUV pulses are sensitive to protein structural evolution. This work provides a protocol for applying multidimensional UV spectroscopy to study protein folding. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
          Cover page: Exploring the Protein Folding Dynamics of Beta3s with Two‐Dimensional Ultraviolet (2DUV) Spectroscopy
          • Article
          • Peer Reviewed
          UC Irvine Previously Published Works (2024)
          Accurately and rapidly acquiring the microscopic properties of a material is crucial for catalysis and electrochemistry. Characterization tools, such as spectroscopy, can be a valuable tool to infer these properties, and when combined with machine learning tools, they can theoretically achieve fast and accurate prediction results. However, on the path to practical applications, training a reliable machine learning model is faced with the challenge of uneven data distribution in a vast array of non-negligible solvent types. Herein, we employ a combination of the first-principles-based approach and data-driven model. Specifically, we utilize density functional theory (DFT) to calculate theoretical spectral data of CO-Ag adsorption in 23 different solvent systems as a data source. Subsequently, we propose a hierarchical knowledge extraction multiexpert neural network (HMNN) to bridge the knowledge gaps among different solvent systems. HMNN undergoes two training tiers: in tier I, it learns fundamental quantitative spectra-property relationships (QSPRs), and in tier II, it inherits the fundamental QSPR knowledge from previous steps through a dynamic integration of expert modules and subsequently captures the solvent differences. The results demonstrate HMNNs superiority in estimating a range of molecular adsorbate properties, with an error range of less than 0.008 eV for zero-shot predictions on unseen solvents. The findings underscore the usability, reliability, and convenience of HMNN and could pave the way for real-time access to microscopic properties by exploiting QSPR.
            Cover page: Spectroscopy-Guided Deep Learning Predicts Solid-Liquid Surface Adsorbate Properties in Unseen Solvents.
            • Article
            • Peer Reviewed
            UC Irvine Previously Published Works (2022)
            Protein secondary structure discrimination is crucial for understanding their biological function. It is not generally possible to invert spectroscopic data to yield the structure. We present a machine learning protocol which uses two-dimensional UV (2DUV) spectra as pattern recognition descriptors, aiming at automated protein secondary structure determination from spectroscopic features. Accurate secondary structure recognition is obtained for homologous (97%) and nonhomologous (91%) protein segments, randomly selected from simulated model datasets. The advantage of 2DUV descriptors over one-dimensional linear absorption and circular dichroism spectra lies in the cross-peak information that reflects interactions between local regions of the protein. Thanks to their ultrafast (∼200 fs) nature, 2DUV measurements can be used in the future to probe conformational variations in the course of protein dynamics.
              Cover page: Machine learning recognition of protein secondary structures based on two-dimensional spectroscopic descriptors
              • Article
              LBL Publications (2002)
                Cover page: Complexation of thorium(IV) with 2-furoic acid and 2-thenoic acid in aqueous solution
                • Article
                • Peer Reviewed
                UC Irvine Previously Published Works (2013)
                The formation of amyloid fibrils is associated with many serious diseases as well as diverse biological functions. Despite the importance of these aggregates, predicting the aggregation propensity of a particular sequence is a major challenge. We report a joint 2D nuclear magnetic resonance (NMR) and ultraviolet (2DUV) study of fibrillization in the wild-type and two aggregation-prone mutants of the eye lens protein γS-crystallin. Simulations show that the complexity of 2DUV signals as measured by their approximate entropy is a good indicator for the conformational entropy and in turn is strongly correlated with its aggregation propensity. These findings are in agreement with high-resolution NMR experiments and are corroborated for amyloid fibrils. The 2DUV technique is complementary to high-resolution structural methods and has the potential to make the evaluation of the aggregation propensity for protein variant propensity of protein structure more accessible to both theory and experiment. The approximate entropy of experimental 2DUV signals can be used for fast screening, enabling identification of variants with high fibrillization propensity for the much more time-consuming NMR structural studies, potentially expediting the characterization of protein variants associated with cataract and other protein aggregation diseases.
                  Cover page: Exploring the aggregation propensity of γS-crystallin protein variants using two-dimensional spectroscopic tools.
                  • Article
                  • Peer Reviewed
                  UC Irvine Previously Published Works (2015)
                  Understanding the exciton dynamics in biological systems is crucial for the manipulation of their function. We present a combined quantum mechanics (QM) and molecular dynamics (MD) simulation study that demonstrates how coherent two-dimensional near-ultraviolet (2DNUV) spectra can be used to probe the exciton dynamics in a mini-protein, Trp-cage. The 2DNUV signals originate from aromatic transitions that are significantly affected by the couplings between residues, which determine exciton transport and energy relaxation. The temporal evolution of 2DNUV features captures important protein structural information, including geometric details and peptide orientations.
                    Cover page: Two-Dimensional Near Ultraviolet (2DNUV) Spectroscopic Probe of Structural-Dependent Exciton Dynamics in a Protein
                    • Article
                    • Peer Reviewed
                    UC Irvine Previously Published Works (2020)
                    Composite structures have been widely utilized to improve material performance. Here we report a semiconductor-metal hybrid structure (CuO/Ag) for CO oxidation that possesses very promising activity. Our first-principles calculations demonstrate that the significant improvement in this system's catalytic performance mainly comes from the polarized charge injection that results from the Schottky barrier formed at the CuO/Ag interface due to the work function differential there. Moreover, we propose a synergistic mechanism underlying the recovery process of this catalyst, which could significantly promote the recovery of oxygen vacancy created via the M-vK mechanism. These findings provide a new strategy for designing high performance heterogeneous catalysts.
                      Cover page: Carbon Monoxide Oxidation Promoted by Surface Polarization Charges in a CuO/Ag Hybrid Catalyst
                      Top