美國川普總統任內友台法案立法過程之研究

2018年3月《台灣旅行法》的立法完成是1979年《台灣關係法》美國對台承諾的賡續，同時作為美國總統川普任內系列友台法案的開端。自川普上任以來，美中關係的惡化與美國印太戰略等國際因素向來為美台關係升溫的討論變數；然而美國國會議員個人因素的討論卻未臻完整，使得友台法案的研究始終缺少個人面向的理解。 本文以既有美國國會台灣連線議員願意支持台灣之影響變數為研究基礎，研究範圍選擇美國川普總統任內三項友台法案為題探討其立法過程，再以微觀角度分析提案議員選區利益、選區人口結構、政黨與意識形態，試圖理解議員個人在友台法案生成中的影響；再者，本文為求當地台美人與議員互動與台美人社群之在地視角，納入在美台灣草根團體台灣人公共事務會 (FAPA) 政策建議端、領導端以及執行端的第一手訪問以求全面且完整的個人層次分析。 在議員個人面，三項法案之主力友台議員均為共和黨保守派，各自代表選區與台灣進出口貿易均在法案形成後有所增加，且雙邊貿易互動穩定；在選區人口面，台裔與中裔人口都互有增減，但是兩項人口佔全州比例微乎其微，因此不足以成為撼動法案生成的變數。最後，透過與FAPA的訪問可知無論是FAPA非營利組織本身或是台美人個人，無不積極為台灣議題遞交請願書並培養與選區國會議員的連結與情誼；加上我國駐美各地外交領事人員在與美國國會交涉與法案內容的鍥而不捨，最終在各方長期且正向的雙邊互動與努力下方得成就友台法案。 最後，本研究發現議員個人選區經濟利益、政黨與意識形態、台美人社群、FAPA與我國駐美單位的大力推動，以及國際環境均為有利於友台法案生成的因素。然而，2022年美國期中選後新局與未來美中關係的變化或將為拜登任內友台法案的新生產生新變數

Velocity dependence of adhesive wear due to asperity plowing

Adhesive wear at sliding contact interfaces is governed by the failure of microscale asperities, influenced by material properties, interfacial adhesion, and sliding velocity. This study investigates the velocity-dependent wear mechanisms at the asperity level using coarse-grained molecular dynamics simulations across a spectrum of materials with tunable adhesion potentials. Our results reveal two distinct regimes: 1) Plasticity-dominated regime. At lower velocities, asperity interactions primarily result in plastic smoothing, leading to a decrease in the wear rate with increasing velocity. This behavior arises due to velocity-dependent contact forces, which exert a stronger influence than the relatively weak velocity dependence of wear volumes. 2) Fracture-dominated regime. Beyond a critical velocity, localized fracture generates debris particles, causing wear volumes to surge and wear rates to increase by orders of magnitude. The transition between these regimes is driven by competition between strain rate hardening and inertial effects. These findings clarify the non-monotonic velocity dependence of wear rates in tribological systems and provide predictive criteria for mitigating wear in engineering applications

Effect of mixed plastic hardening on the cyclic contact between a sphere and a rigid flat

Abstract This paper studies the effect of mixed plasticity mode (combined with isotropic and kinematic hardening law) on the cyclic contact between an elastic-plastic sphere and a rigid flat. Assuming power-law hardening with different levels of mixed plasticity for the sphere, we derived a semi-analytical expression of load versus interference during the first loading and unloading process. During cyclic loading, our results indicate that the isotropic plasticity model shows no variation of residual interference, while kinematic plasticity has the cyclic effect on the residual interference, and this effect is bigger for the material with a higher hardening exponent. In addition, we provided the semi-analytical expression for the evolution of residual interference, which is accurate for the strain hardening exponent from 0.1 to 0.5

Using spherical indentation to determine creep behavior with considering empirical friction coefficient

Indentation testing is a common technique for characterizing the mechanical properties of materials. When it comes to assessing the yield behavior of metals, conical indentation is often favored due to its ability to induce significant plastic deformation at relatively shallow indentation depths. On the other hand, spherical indentation is typically chosen for evaluating metal creep behavior, as it helps minimize the influence of plastic deformation on creep measurements. In spherical indentation tests, the friction at the contact interface is particularly crucial, given the larger contact area and more pronounced slip zones. However, accurately determining the friction coefficient at the contact interface is a complex multi-scale challenge, with the exact coefficient varying based on specific testing conditions and surface treatments. Consequently, empirical friction coefficients are frequently employed, often without thorough justification. In this work, we proposed Bayesian inference method for obtaining the creep constitutive behavior of alloys through spherical indentation tests. Our model considers not only the complexity of creep law, but also the indentation friction, which is unable to consider in most spherical indentation tests with traditional treatment. By using experimental data of spherical indentation tests on 310S stainless steel and pure nickel alloy from literature, present study demonstrates the effectiveness of the Bayesian inference approach, with the inferred constitutive models exhibiting well agreement with uniaxial creep behavior. Furthermore, the method considers the friction coefficient as an extra factor in inferring creep constitutive behavior from indentation tests

A revised Chaboche model from multiscale approach to predict the cyclic behavior of type 316 stainless steel at room temperature

In this work, we propose a revised Chaboche model based on a crystal plasticity multiscale approach. From our experiments, 316L steel exhibits two plasticity characteristics at room temperature during the cyclic loading: varied plastic modulus in strain-controlled cycling and continuous growing ratcheting strain in stress-controlled cycling. These characteristics cannot be predicted by using the classic Chaboche model. To modify this model, we used a crystal plasticity multiscale approach to see the microstructure effect on these characteristics. The result shows that the viscous effect, which is ignored in the classic model, plays an important role in stress-controlled cycling. With the multiscale simulation results, we revise the Chaboche model in two folds: a static recovery item is included in the kinematic hardening rule to consider the influence of viscosity on ratcheting; the dynamic recovery term is varied with the accumulated plastic strain for the change of plastic modulus during the straincontrolled cycling. With the revised model, we show that the strain- and stress-controlled cyclic behaviors from experiments can be well predicted. Also, the application of the revised model in integrated structural analysis is discussed

核用钢高温力学性能及本构模型综述

为发展适用于结构完整性评定的高温非弹本构模型，本文对316奥氏体不锈钢和9Cr-1Mo钢高温力学性能及非弹本构模型进行了综述。通过比较单轴拉伸、应变控制循环、蠕变以及塑变-蠕变交互性能，展示了两类核用钢高温力学行为的异同。其中，温度、加载速率、应力水平等对核用钢高温力学性能均有影响。另外，综合评价了用于描述核用钢高温力学性能的两类非弹本构模型，并对模型发展趋势进行了讨论。对核用钢高温力学性能综合准确描述有助于解决工程中核反应堆结构完整评价问题

基於生理感測及機器學習技術之智慧輸液系統

&lt;p&gt;為因應逐漸升高的護病比與提升病患的照護品質，本研究將針對靜脈注射這項常見的醫療處置，配合物聯網與機器學習，設計一套具有以下三項功能的系統：1.能夠實時呈現患者生理數據的網頁, 2.量測與控制輸液速度的裝置, 3.以機器學習發出輸液速度建議及發出患者身體異常的提醒。在前端硬體裝置的部分，本研究採用Arduino作為前端感測器的物聯網通訊平台，透過無線網路傳送前端裝置測得的數據與接收後端發送的指令。在後端的部分採用Node.js架設物聯網與網頁伺服器，達成即時的數據顯示與遠端控制。為了進一步加速患者生理情況之判讀，此系統亦加入機器學習將讀取到的資料進行分析，以幫助護理人員提供患者更快速且精確的醫療處置，透過科技輔助達成精準地輸液照護。&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt; </jats:p

視覺化場域內人員生理狀況監控系統之設計與實現

&lt;p&gt;近年來，心臟疾病的患者年齡逐年下降，而死亡率最高的心肌梗塞的前兆多為心肌缺血。傳統上的心臟疾病檢測方法無法提供醫療照護者一套即時且有效的監測方式，造成無法適時進行醫療措施。本論文提出一種可即時AR視覺化方式監測場域中人員生理狀況，在穿戴式裝置上直接進行特徵的計算與心電訊號判讀，考慮到RGB攝影機有隱私權的爭議，結合 RPLiDAR 與慣性穿戴裝置之身分辨識系統，可以對場域內人員進行身份辨識與追蹤，接著透過AR視覺化技術於監控畫面上即時顯示每位受照護人員的生理狀況，每位人員的生理感測資訊即時地被紀錄與執行特徵分析。透過機器學習模型判斷心肌缺血與基於感測融合之身份辨識技術，當受照護者的生理狀況異常的時，會即時呈現於監控視窗，協助醫療照護者預防緊急狀況。根據實驗結果，本系統所開發的演算法較其他演算法準確且具效率。&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;In recent year, the age of patients with heart disease has been decreasing year by year. Myocardial ischemia is the symptom of myocardial infarction, which has the highest mortality rate among heart diseases. Traditional methods can-not provide medical caregivers with a set of immediate and effective monitoring methods, which can hardly provide immediate medical measurement. As a result, we propose an instant AR visualization method to monitor the physiological condition of people in these field to develop the calculation of features and the interpretation of cardiac signals on wearable de-vice. Considering the controversy over the privacy of RGB cameras, we combine RPLiDAR to develop an inertial wearable device identity recognition system, which can identify and track the people in the field. Each person’s physio-logical sensory information is instantly recorded and characterized, which makes medical care-givers monitor at any time clearly and quickly. Through using machine learning model to determine myocardial ischemia and sensor-based fusion of identity recognition technology, it will actively issue alerts when the care recipient’s physiological condition is abnormal and to assist healthcare provider in preventing possible emergency situations. In the experimental evaluation, the algorithms developed in this system are more accurate and efficient than other algorithms.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt; </jats:p

Machine learning informed visco-plastic model for the cyclic relaxation of 316H stainless steel at 550 °C

Among the structural alloys for this fast reactor, 316H stainless steel has emerged as a promising candidate. Because the operating temperature of Sodium-cooled reactor is specifically designed to be 550 degrees C, this operating temperature triggers material inelastic behavior depends more on the coupling of fatigue and creep, which complicates the constitutive model. By introducing static recovery terms, previous studies could capture some experimental features, but failed to describe the interaction by fatigue and creep. In this work, in order to describe the fatigue and creep during cyclic relaxation of 316H stainless steel at 550 degrees C, we propose a modified visco-plastic constitutive model within the framework of unified Chaboche model. In the proposed model, the parameters related to the static recovery items are coupled, and thus cannot be identified from experiments using the traditional trial and error. To address this issue, we employed the Bayesian approach to identify these parameters. The parameter identification involves two steps: (i) con-structing a Gaussian Process surrogate model using data generated from the finite element method, and (ii) obtaining the value of parameters through Markov Chain Monte Carlo sampling under the Bayesian framework. The proposed procedure, is demonstrated by the using experi-mental results of 316H stainless steel at 550 degrees C. Under the coupling of fatigue-creep, the material exhibits a cyclic-dependent accelerated stress relaxation before reaching the saturated stage and a steady state of relaxed stress after a long holding time. These mechanical responses are well predicted by the proposed model. Further, we conducted two kinds of multi-axial cyclic test, tensile test of notched bar and coupled tensile-torsion test, to validate the proposed constitutive model for the cyclic behavior under the multi-axial stress state.</p