EXPERIMENTAL RESEARCH ON THE VIBRATION CHARACTERISTICS OF BRIDGE'S HORIZONTAL ROTATION SYSTEM

As a new construction method, the bridge horizontal rotation construction method can reduce the impact of traffic under the bridge. During the horizontal rotation of the bridge, the overall structure will inevitably lead to a vibration response due to the construction error of the contact surface of the spherical hinge. Due to the large weight of the structure and the longer cantilever of the superstructure, the vibration at the spherical hinge will be amplified at the girder end, which will adversely affect the stability of the structure. Taking a 10,000-ton rotating bridge as a reference, a scaled model was made to test the vibration of the girder during the rotating process of the horizontal rotating system.And by analyzing the frequency domain curve of girder vibration and the results of simulation calculation, it is found that the vertical vibration displacement response is related to the first three modes of longitudinal bending of the girder structure, but has nothing to do with the higher modes or other modes. Applying the harmonic response analysis module in ANSYS software method, it is proposed that the structural vibration effect will reach the smallest by controlling the rotating speed in order to control the excitation frequency within the first-order mode frequency of girder. Also in this research, the expression of the relationship between the vertical vibration velocity and acceleration of the girder end of the horizontal rotation system and the vibration frequency of the girder is established. Based on that, it is proposed that the stability of the horizontal rotation can be predicted by monitoring the vertical velocity and acceleration of the cantilever girder end during the horizontal rotation

MECHANICAL BEHAVIOR OF HORIZONTAL SWIVEL SYSTEM WITH UHPC SPHERICAL HINGE UNDER SEISMIC ACTION

In the process of rotation, the total weight of the bridge structure is jointly supported by the spherical hinge and the supporting structure, and its lateral stability is poor. It is easy to lose stability under the action of dynamic loads such as seismic action effect. The present paper takes a 10,000-ton continuous rigid frame swivel bridge as the re-search object, analyzes the dynamic response of the seismic action to the horizontal swivel system, and establishes several structure simulation models. Eighteen seismic waves in three directions that meet the calculation requirements are screened for time history analysis and compared with the response spectrum method. Finally, an optimization algorithm for the seismic response of the bridge under horizontal swivel system is proposed based on the mode superposition method. The UHPC spherical hinge bears all the vertical forces and 20% of the bending moment caused by the seismic action, the support structure bearing the remaining 80% of the bending moment. The optimization algorithm proposed in this paper features high accuracy

Instruction Mining: When Data Mining Meets Large Language Model Finetuning

Large language models (LLMs) are initially pretrained for broad capabilities and then finetuned with instruction-following datasets to improve their performance in interacting with humans. Despite advances in finetuning, a standardized guideline for selecting high-quality datasets to optimize this process remains elusive. In this paper, we first propose InstructMining, an innovative method designed for automatically selecting premium instruction-following data for finetuning LLMs. Specifically, InstructMining utilizes natural language indicators as a measure of data quality, applying them to evaluate unseen datasets. During experimentation, we discover that double descent phenomenon exists in large language model finetuning. Based on this observation, we further leverage BlendSearch to help find the best subset among the entire dataset (i.e., 2,532 out of 100,000). Experiment results show that InstructMining-7B achieves state-of-the-art performance on two of the most popular benchmarks: LLM-as-a-judge and Huggingface OpenLLM leaderboard.Comment: 22 pages, 7 figure

API-Assisted Code Generation for Question Answering on Varied Table Structures

A persistent challenge to table question answering (TableQA) by generating executable programs has been adapting to varied table structures, typically requiring domain-specific logical forms. In response, this paper introduces a unified TableQA framework that: (1) provides a unified representation for structured tables as multi-index Pandas data frames, (2) uses Python as a powerful querying language, and (3) uses few-shot prompting to translate NL questions into Python programs, which are executable on Pandas data frames. Furthermore, to answer complex relational questions with extended program functionality and external knowledge, our framework allows customized APIs that Python programs can call. We experiment with four TableQA datasets that involve tables of different structures -- relational, multi-table, and hierarchical matrix shapes -- and achieve prominent improvements over past state-of-the-art systems. In ablation studies, we (1) show benefits from our multi-index representation and APIs over baselines that use only an LLM, and (2) demonstrate that our approach is modular and can incorporate additional APIs.Comment: EMNLP 2023 camera ready, 13 pages, 11 figure

Boryl Participation in the Bond Activation Reactions by PBP Type Iridium and Rhodium Complexes and Application in Selective C-H Alkylation of Pyridines

Pincer ligands are commonly utilized in the design of transition metal catalysts. Our group recently reported the synthesis of diarylboryl-based Ir and Rh complexes, which feature an X-type boryl ligand that is Lewis acidic. Herein, we explored the properties and reactivity of Ag, Ir and Rh metal complexes that feature boryl or borane ligand. In Chapter II, silver halide complexes of a borane/bis(phosphine) ligand were prepared and characterized. With AgF, the borane abstracts fluoride, resulting in a zwitterionic complex. With AgCl, AgBr, and AgI, the halide stays coordinated to Ag, with little to no Ag–B interaction. In Chapter III, H–X bond addition across the Ir–B unit of the previously reported (PBP)Ir(CO)₂ were examined. Water, methanol, ethanol, cyclohexanol, phenols, benzoic acid, and triethylamine trihydrofluoride added the O–H and F–H units across the Ir–B bond, resulting in dicarbonyl complexes with Ir–H and B–O/F bonds. Thermolysis of (PBP)Ir(CO)₂ with n-butylamine resulted in a monocarbonyl product of N-H addition. Two possible mechanisms were proposed, and mechanistic experiments were conducted to study this system. In Chapter IV, reactions of (PBP)Ir complexes with ethylene were examined. (PBP)IrH₄, (PBP)IrH₂(CO), and (PBP)Ir(CO)₂ activated the C–H bond in ethylene to form unique products that have the elements of ethylene incorporated into the molecules and resulted in B–C bonds. These reactions demonstrate that the boryl donor is not merely an electronically unique central donor with Lewis acidic properties. It also participates in the activation of C–H bonds by the metal center and forms B–C bond in the product. In Chapter V, we examined selective C–H activation of pyridines with (PBP)Rh and (PBP)Ir complexes. We observed the isomerism derived from the 2-pyridyl fragment connecting either via B-N/C-M bonds or via B-C/N-M bonds. This M-C/M-N isomerism was systematically examined for four structural Types, totaling 16 compounds. Several of these compounds were isolated or observed in solution by experimental methods, in addition to a few 2-quinolyl variants. The DFT predictions concerning the thermodynamic preference within each M-C/M-N isomeric match the experimental findings very well. In Chapter VI, we utilized (PBP)Rh complexes synthesized in Chapter V to catalyze norbornylation of substrates containing pyridyl groups. For substrates such as pyridine, quinoline, 4-tert-butylpyridine, 4-dimethylaminopyridine, and 3-ethylpyridine, the norbornylation happened at the pyridine ortho position. However, for 2-tolylpyridine, the norbornylation happened on the tolyl group

Silence

Senior Project submitted to The Division of Arts of Bard College

Offloading operation bivariate extreme response statistics for FPSO vessel

The Floating Production Storage and Offloading unit (FPSO) is an offshore unit producing and storing crude oil prior to tanker transport. An important design concern is an accurate prediction of risky dynamic hawser tensions during FPSO offloading operations. Bivariate extreme hawser tension contours are important for selecting proper design values. This paper employed the AQWA hydrodynamic software to analyze vessel hydrodynamic wave loads dynamic response, acting on FPSO vessels under realistic sea state conditions. This paper presents an efficient method for estimating FPSO bivariate response statistics based on numerical simulations validated by various experiments. The bivariate Average Conditional Exceedance Rate (ACER2D) method offers an accurate bivariate extreme value probability distribution and return period contours estimation, utilizing available data efficiently. The two-dimensional probability contours, corresponding to low probability return periods, are easily obtained by the ACER2D method. The performance of the presented method has shown that the ACER2D method provides an efficient and accurate prediction of extreme return period contours. The suggested approach may be used for FPSO vessel design, minimizing potential FPSO hawser damage. Bivariate contours yield bivariate design points, as opposed to a pair of uncoupled univariate design points with the same return period as currently adopted in the industry.publishedVersio

A time-series model for estimating temporal variation in phenotypic selection on laying dates in a Dutch great tit population

1. Temporal and spatial variation in phenotypic selection due to changing environmental conditions is of great interest to evolutionary biologists, but few existing methods estimating its magnitude take into account the temporal autocorrelation. 2. We use state‐space models (SSMs) to analyse phenotypic selection processes that cannot be observed directly and use Template Model builder (TMB), an R package for computing and maximizing the Laplace approximation of the marginal likelihood for SSM and other complex, nonlinear latent variable model via automatic differentiation. Using a long‐term great tit (Parus major) dataset, we fit several SSMs and conduct model selection based on Akaike information criterion (AIC) to assess the support for fluctuated directional or autocorrelated stabilizing selection on breeding time of the great tit population. 3. Our results show that there is directional selection on the probability of breeding failure, and stabilizing selection on the mean number of fledglings. This selection for early laying date is consistent with a previous study of the same population. We also estimate the variation and autocorrelation in other parameters of the fitness functions, including the width and height, and found the height and location of annual fitness function are autocorrelated with significant variation, while the width can be assumed to constant over time. 4. Using TMB to fit SSMs, we are able to estimate additional parameters compared to previous methods, all without requiring a substantial increase in computational resources. Furthermore, our specification of complex nonlinear model structure benefits greatly from the flexibility of model formulation with TMB. Therefore, our approach could be directly applied to estimating even more complicated phenotypic selection processes induced by environmental change for other species

R code for simulation study

The details of the simulation study are given in the Supporting Information