Harnessing the Melting Peculiarities of Ultra‐High Molecular Weight Polyethylene Fibers for the Processing of Compacted Fiber Composites

Summary: Compacted fiber composites offer unique properties due to their lack of an extraneous matrix. The conditions of processing ultra‐high molecular weight polyethylene (UHMWPE) fibers were simulated in a heated pressure cell. In situ X‐ray diffraction measurements were used to follow the relevant transitions and the changes in the degree of crystallinity during melting and crystallization. The results strongly support the suggestion that the hexagonal crystal phase, in which the chain conformation is extremely mobile on the segmental level, constitutes the physical basis of compaction technologies for processing UHMWPE fibers into a single‐polymer composite. This report suggests that using a pseudo‐phase diagram outlining the occurrence of different phases during slow heating and the degree of crystallinity can provide valuable insight into the technological parameters relevant for optimal processing conditions.

Degree of crystallinity as a function of pressure and temperature in a region relevant to compaction processes.     

Effective deadlock resolution with self-interested partially-rational agents

This paper pertains to distributed deadlock resolution in settings populated with self-interested bounded-rational autonomous agents. In particular it reports the results of extensive experimentation with 66 agents, each using a deadlock resolution strategy developed and maintained throughout the experiment by a different human decision maker. While from the game-theoretic perspective a simple equilibrium-based solution can be engineered for the problem, it is shown that such a solution fails to hold with bounded-rational agents, even when its principles are thoroughly explained to the individuals that maintain the agents’ strategies. Instead, we show that the system converges to a steady-state, in which the agents use a rich set of different strategies, varying in their performance, as each of them has a different belief regarding its ability to improve, based on the behaviors of the others. To improve system performance, we develop and implement a restructuring heuristic that changes the input each agent receives, as a means of affecting the agents’ decisions to better align with the desired solution. The restructured deadlock presented to each agent is based on former deadlocks it had experienced. Our experiments demonstrate the effectiveness of the restructuring heuristic in facilitating a new steady-state in which the system as a whole substantially improves its performance. The efficiency of the method, in terms of the size of the set of former experiences required for effectively restructuring the agents’ input, is demonstrated through a comparison with a neural network implementation of input restructuring, showing a substantial advantage to the restructuring heuristic.     

The effectiveness of Light Rail transit in achieving regional CO<Subscript>2</Subscript> emissions targets is linked to building energy use: insights from system dynamics modeling

Cities worldwide face the challenges of accommodating a growing population, while reducing emissions to meet climate mitigation targets. Public transit investments are often proposed as a way to curb emissions while maintaining healthy urban economies. However, cities face a system-level challenge in that transportation systems have cascading effects on land use and economic development. Understanding how an improved public transit system could affect urban growth and emissions requires a system-level view of a city, to anticipate side effects that could run counter to policy goals. To address this knowledge gap, we conducted a case study on the rapidly growing Research Triangle, North Carolina (USA) region, which has proposed to build a Light Railway by 2026 along a heavily used transportation corridor between the cities of Durham and Chapel Hill. At the same time, Durham County has set a goal of lowering greenhouse gas emissions by 30% from a 2005 baseline by 2030. In collaboration with local stakeholders, we developed a system dynamics model to simulate how Light Rail transit and concurrent policies could help or hinder these sustainable growth goals. The Durham–Orange Light Rail Project (D–O LRP) model simulates urban–regional dynamics between 2000 and 2040, including feedbacks from energy spending on economic growth and from land scarcity on development. Counter to expectations, model scenarios that included Light Rail had as much as 5% higher regional energy use and CO₂ emissions than business-as-usual (BAU) by 2040 despite many residents choosing to use public transit instead of private vehicles. This was largely due to an assumption that Light Rail increases demand for commercial development in the station areas, creating new jobs and attracting new residents. If regional solar capacity grew to 640 MW, this would offset the emissions growth, mostly from new buildings, that is indirectly due to Light Rail. National trends in building and automobile energy efficiency, as well as federal emissions regulation under the Clean Power Plan, would also allow significant progress toward the 2030 Durham emissions reduction goal. By simulating the magnitude of technology and policy effects, the D–O LRP model can enable policy makers to make strategic choices about regional growth.     

On controllability and trajectory tracking of a kinematic vehicle model

This paper presents some further results concerning the issues of controllability and trajectory tracking regarding a front-wheel drive vehicle kinematic model. A simple procedure for computing an open-loop control strategy that transfers the system between given initial and final states, is presented. In particular, the input function is computed by means of a set of linear algebraic equations. The resulting motion planning procedure allows us to present a control scheme for solving the trajectory (a time-parameterized reference signal) tracking problem. Various applications of the approach in forward and backward motions are considered, and simulation results are presented.     

Quantitative characterization of extruded film texture

Quantitative characterization of the texture of extruded low density polyethylene films was attempted with the aid of concepts such as the scale and intensity of segregation. The scale of segregation defined along a line and the profile of the scale of segregation were found to be useful modifications of the originally defined scale of segregation. The former, which is obtained by taking concentration points along a line, was needed because the film texture is non-isotropic, while the latter, which is obtained by repeated calculations of the scale of segregation over a varying size sample was needed, for a more accurate representation of this texture. The profile of the scale of segregation leads to a few typical values, which perhaps, can be related to particular features of the mixing mechanisms in the extruder.     

Fast computation of limit cycles in an industrial application

A model problem is described that requires the study of a system of the form v(t) = F _P (v(t), t) which depends on a set of parameters P, and where 1. The problem comes from an industrial application where it is a kernel of an optimization procedure. The optimization depends on computing the limit cycle, and the problem needs to be solved repeatedly. Short computation time is therefore essential. The naive approach is to integrate the equation forward in time, starting from an arbitrary initial condition, until the transients disappear and the limit cycle is approximated within a given tolerance. This approach is too slow and thus impractical in the context of the optimization procedure. The problem involves two types of asymptotic considerations: long-time asymptotics and small-parameter asymptotics. Here a simple approach is demonstrated, based on implementing the averaging method. This reduces the solution time to the point that the optimization procedure becomes feasible.     

Clearance of chylomicron remnants in normolipidaemic patients with coronary artery disease: case control study over three years

OBJECTIVE: To test the hypothesis that subjects who clear chylomicron remnants slowly from plasma may be at higher risk of coronary artery disease than indicated by their fasting plasma lipid concentrations. DESIGN: Case control study over three years. SETTING: An 800 bed general municipal hospital. SUBJECTS: 85 normolipidaemic patients with coronary artery disease selected prospectively and matched with 85 normolipidaemic subjects with normal coronary arteries on angiography. INTERVENTIONS: All subjects were given a vitamin A fat loading test which specifically labels intestinal lipoproteins with retinyl palmitate. MAIN OUTCOME MEASURE: Postprandial lipoprotein metabolism. RESULTS: The area below the chylomicron remnant retinyl palmitate curve was significantly increased in the coronary artery disease group as compared with the controls (mean 23.4 (SD 15.0) v 15.3 (8.9) mumol/l.h; 95% confidence interval of difference 4.37 to 11.82). CONCLUSION: Normolipidaemic patients with coronary artery disease had significantly higher concentrations of chylomicron remnants in plasma than normolipidaemic subjects with normal coronary vessels. This may explain the mechanism underlying the susceptibility to atherosclerosis of coronary artery disease patients with normal fasting lipid values. As diet and drugs can ameliorate the accumulation of postprandial lipoproteins in plasma, the concentration of chylomicron remnants should be measured in patients at high risk of coronary artery disease.     

冶炼烟气净化：所有步骤在一台设备内完成

介绍Kimre公司的SXF^TM半错流洗涤器的结构、优点和应用。该洗涤器采用卧式并流气液接触方式,可根据需要分隔成不同操作段,在由交织单丝构成的纤维介质上完成气体的冷却、净化和除沫。与传统立式逆流填料塔相比,该洗涤器的优点为：高度低,泵、阀门、控制器等可在地面安装,容易操作和维修;液气比范围宽;可进行多级操作,包括在一台设备内完成多个化学过程。如用于冶炼烟气净化,所有步骤可在一台设备内完成。列举了化肥厂造粒塔气体净化、磷酸厂气体除氟和硫酸厂干燥塔除沫等应用实例。     

Macroscale Biomolecular Electronics and Ionics

The conduction of ions and electrons over multiple length scales is central to the processes that drive the biological world. The multidisciplinary attempts to elucidate the physics and chemistry of electron, proton, and ion transfer in biological charge transfer have focused primarily on the nano‐ and microscales. However, recently significant progress has been made on biomolecular materials that can support ion and electron currents over millimeters if not centimeters. Likewise, similar transport phenomena in organic semiconductors and ionics have led to new innovations in a wide variety of applications from energy generation and storage to displays and bioelectronics. Here, the underlying principles of conduction on the macroscale in biomolecular materials are discussed, highlighting recent examples, and particularly the establishment of accurate structure–property relationships to guide rationale material and device design. The technological viability of biomolecular electronics and ionics is also discussed.