Hot Tearing in Cast Aluminum Alloys: Measures and Effects of Process Variables

Hot tearing is a common and severe defect encountered in alloy castings and perhaps the pivotal issue defining an alloy\u27s castability. Once it occurs, the casting has to be repaired or scraped, resulting in significant loss. Over the years many theories and models have been proposed and accordingly many tests have been developed. Unfortunately many of the tests that have been proposed are qualitative in nature; meanwhile, many of the prediction models are not satisfactory as they lack quantitative information, data and knowledge base. The need exists for a reliable and robust quantitative test to evaluate/characterize hot tearing in cast alloys. This work focused on developing an advanced test method and using it to study hot tearing in cast aluminum alloys. The objectives were to: 1) develop a reliable experimental methodology/setup to quantitatively measure and characterize hot tearing; and 2) quantify the mechanistic contributions of the process variables and investigate their effects on hot tearing tendency. The team at MPI in USA and CANMET-MTL in Canada has collaborated and developed such a testing setup. It consists mainly of a constrained rod mold and the load/displacement and temperature measuring system, which gives quantitative, simultaneous measurements of the real-time contraction force/displacement and temperature during solidification of casting. The data provide information about hot tearing formation and solidification characteristics, from which their quantitative relations are derived. Quantitative information such as tensile coherency, incipient crack refilling, crack initiation and propagation can be obtained. The method proves to be repeatable and reliable and has been used for studying the effects of various parameters (mold temperature, pouring temperature and grain refinement) on hot tearing of different cast aluminum alloys. In scientific sense this method can be used to study and reveal the nature of the hot tearing, for industry practice it provides a tool for production control. Moreover, the quantitative data and fundamental knowledge gained in this thesis can be used for validating and improving the existing hot tearing models

Geometric Algorithms for Intervals and Related Problems

In this dissertation, we study several problems related to intervals and develop efficient algorithms for them. Interval problems have many applications in reality because many objects, values, and ranges are intervals in nature, such as time intervals, distances, line segments, probabilities, etc. Problems on intervals are gaining attention also because intervals are among the most basic geometric objects, and for the same reason, computational geometry techniques find useful for attacking these problems. Specifically, the problems we study in this dissertation includes the following: balanced splitting on weighted intervals, minimizing the movements of spreading points, dispersing points on intervals, multiple barrier coverage, and separating overlapped intervals on a line. We develop efficient algorithms for these problems and our results are either first known solutions or improve the previous work. In the problem of balanced splitting on weighted intervals, we are given a set of n intervals with non-negative weights on a line and an integer k ≥ 1. The goal is to find k points to partition the line into k + 1 segments, such that the maximum sum of the interval weights in these segments is minimized. We give an algorithm that solves the problem in O(n log n) time. Our second problem is on minimizing the movements of spreading points. In this problem, we are given a set of points on a line and we want to spread the points on the line so that the minimum pairwise distance of all points is no smaller than a given value δ. The objective is to minimize the maximum moving distance of all points. We solve the problem in O(n) time. We also solve the cycle version of the problem in linear time. For the third problem, we are given a set of n non-overlapping intervals on a line and we want to place a point on each interval so that the minimum pairwise distance of all points are maximized. We present an O(n) time algorithm for the problem. We also solve its cycle version in O(n) time. The fourth problem is on multiple barrier coverage, where we are given n sensors in the plane and m barriers (represented by intervals) on a line. The goal is to move the sensors onto the line to cover all the barriers such that the maximum moving distance of all sensors is minimized. Our algorithm for the problem runs in O(n2 log n log log n + nm log m) time. In a special case where the sensors are all initially on the line, our algorithm runs in O((n + m) log(n + m)) time. Finally, for the problem of separating overlapped intervals, we have a set of n intervals (possibly overlapped) on a line and we want to move them along the line so that no two intervals properly intersect. The objective is to minimize the maximum moving distance of all intervals. We propose an O(n log n) time algorithm for the problem. The algorithms and techniques developed in this dissertation are quite basic and fundamental, so they might be useful for solving other related problems on intervals as well

Dispersing Points on Intervals

We consider a problem of dispersing points on disjoint intervals on a line. Given n pairwise disjoint intervals sorted on a line, we want to find a point in each interval such that the minimum pairwise distance of these points is maximized. Based on a greedy strategy, we present a linear time algorithm for the problem. Further, we also solve in linear time the cycle version of the problem where the intervals are given on a cycle

Separating Overlapped Intervals on a Line

Given n intervals on a line ℓ, we consider the problem of moving these intervals on ℓ such that no two intervals overlap and the maximum moving distance of the intervals is minimized. The difficulty for solving the problem lies in determining the order of the intervals in an optimal solution. By interesting observations, we show that it is sufficient to consider at most n candidate lists of ordered intervals. Further, although explicitly maintaining these lists takes Ω(n2) time and space, by more observations and a pruning technique, we present an algorithm that can compute an optimal solution in O(n log n) time and O(n) space. We also prove an Ω(n log n) time lower bound for solving the problem, which implies the optimality of our algorithm

On the limit cycles of planar discontinuous piecewise linear differential systems with a unique equilibrium

This paper deals with planar discontinuous piecewise linear differential systems with two zones separated by a vertical straight line x = k. We assume that the left linear differential system (x k) share the same equilibrium, which is located at the origin O(0, 0) without loss of generality. Our results show that if k = 0, that is when the unique equilibrium O(0, 0) is located on the line of discontinuity, then the discontinuous piecewise linear differential systems have no crossing limit cycles. While for the case k ≠ 0 we provide lower and upper bounds for the number of limit cycles of these planar discontinuous piecewise linear differential systems depending on the type of their linear differential systems, i.e. if those systems have foci, centers, saddles or nodes, see Table 2

On Choosing Initial Values of Iteratively Reweighted ℓ1\ell_1 Algorithms for the Piece-wise Exponential Penalty

Computing the proximal operator of the sparsity-promoting piece-wise exponential (PiE) penalty $1-e^{-|x|/\sigma}$ with a given shape parameter $\sigma>0$, which is treated as a popular nonconvex surrogate of $\ell_0$-norm, is fundamental in feature selection via support vector machines, image reconstruction, zero-one programming problems, compressed sensing, etc. Due to the nonconvexity of PiE, for a long time, its proximal operator is frequently evaluated via an iteratively reweighted $\ell_1$ algorithm, which substitutes PiE with its first-order approximation, however, the obtained solutions only are the critical point. Based on the exact characterization of the proximal operator of PiE, we explore how the iteratively reweighted $\ell_1$ solution deviates from the true proximal operator in certain regions, which can be explicitly identified in terms of $\sigma$, the initial value and the regularization parameter in the definition of the proximal operator. Moreover, the initial value can be adaptively and simply chosen to ensure that the iteratively reweighted $\ell_1$ solution belongs to the proximal operator of PiE

Homomorphic signcryption with public plaintext-result checkability

Signcryption originally proposed by Zheng (CRYPTO \u27 97) is a useful cryptographic primitive that provides strong confidentiality and integrity guarantees. This article addresses the question whether it is possible to homomorphically compute arbitrary functions on signcrypted data. The answer is affirmative and a new cryptographic primitive, homomorphic signcryption (HSC) with public plaintext-result checkability is proposed that allows both to evaluate arbitrary functions over signcrypted data and makes it possible for anyone to publicly test whether a given ciphertext is the signcryption of the message under the key. Two notions of message privacy are also investigated: weak message privacy and message privacy depending on whether the original signcryptions used in the evaluation are disclosed or not. More precisely, the contributions are two-fold: (i) two different definitions of HSC with public plaintext-result checkability is provided for arbitrary functions in terms of syntax, unforgeability and message privacy depending on if the homomorphic computation is performed in a private or in a public evaluation setting, (ii) two HSC constructions are proposed: one for a public evaluation setting and another for a private evaluation setting and security is formally proved

Spatial Evolution of the Effects of Urban Heat Island on Residents\u27 Health

Rising summer temperatures caused by the urban heat island (UHI) has considerable effects on the physical and mental health of urban residents globally. To categorize residents’ health risk areas and evaluate the characteristics of urban spatial evolution, based on data analysis methods, such as ArcGIS, ENVI software, and geostatistical analysis, data from meteorological stations, satellite images, and electronic maps were used to investigate spatial evolution and the process by which UHI affects the respiratory, circulatory, and cardiovascular systems and emotional health of the residents of Tianjin. Results show the UHI significantly increases respiratory, circulatory, and cardiovascular diseases. The emotional health of residents is also significantly affected with the affected level moving from level 1 to level 2-4. Highly concentrated areas in the urban center and patches with high health risks are found to be scattered and fragmented, as indicated by the phased pattern of spatially deteriorating hotspots. Hotspots expansion occurs unidirectionally to the south, surrounding the city center, while shrinking from the inside to the outside. The study identifies urban health space risks and provides theoretical guidance for urban space optimization and healthy urban planning

Comparing Urban and Rural Vulnerability to Heat-Related Mortality: A Systematic Review and Meta-Analysis

Studies of the adverse impacts of high temperature on human health have primarily focused on urban areas, due in part to urban centers generally having higher population density and often being warmer than surrounding rural areas (the “urban heat island” effect). As a result, urban areas are often considered to be more vulnerable to summer heat. However, heat vulnerability may not only be determined by heat exposure, but also by other population characteristics such as age, education, income, baseline health status, and social isolation. These factors are likely to increase vulnerability among rural populations compared to urban populations. In this exploratory study, we compare the vulnerability to heat-related mortality between rural and urban communities through a systematic review and meta-analysis of existing epidemiological studies, based on the idea that urbanicity can be considered as a “combined” indicator of climate variables and socioeconomic variables. We searched studies that examined the association between high ambient temperature and mortality in both rural and urban settings published between 2000 and 2017. A random-effects meta-analysis of Ratios of Relative Risks (RRR) of heat-related mortality in rural compared to urban areas (RRrural/RRurban) was performed. The pooled RRR was 1.033 (95% CI = 0.969, 1.103), which indicates that the rural relative risk is about 3.3% larger than the urban relative risk. Heterogeneity measures show considerable heterogeneity across studies. Our findings suggest that vulnerability to heat-related mortality in rural areas is likely to be similar to or even greater than urban areas. More studies, particularly studies in developing nations, are needed to understand rural vulnerability to heat hazards as a basis for providing better guidance for heat action plans