An aerothermodynamic design optimization framework for hypersonic vehicles

In the aviation field great interest is growing in passengers transportation at hypersonic speed. This requires, however, careful study of the enabling technologies necessary for the optimal design of hypersonic vehicles. In this framework, the present work reports on a highly integrated design environment that has been developed in order to provide an optimization loop for vehicle aerothermodynamic design. It includes modules for geometrical parametrization, automated data transfer between tools, automated execution of computational analysis codes, and design optimization methods. This optimization environment is exploited for the aerodynamic design of an unmanned hypersonic cruiser flying at M∞=8 and 30 km altitude. The original contribution of this work is mainly found in the capability of the developed optimization environment of working simultaneously on shape and topology of the aircraft. The results reported and discussed highlight interesting design capabilities, and promise extension to more challenging and realistic integrated aerothermodynamic design problems

Action Research in Contexts of Change and Inequality

The first purpose of this chapter is to discuss research in education within the international context of change and inequality. In a previous chapter, Atweh and Arias (1991) discussed action research in education both as an appropriate research methodology and as a means of professional development of teachers. Similarly, Atweh (2004) posited action research as a methodology consistent with sociocultural approaches in education. That chapter discussed arguments for the use of action research in the discipline and outlined some of its characteristics. The discussion presented in those chapters did not contextualise their arguments within the international context of countries experiencing rapid changes, nor with regard to countries where poverty and lack of resources are major hindrances for developing research programs in the field. This contextualisation is the second purpose of this current chapter. The next section of this chapter identifies three major current trends in global society and education that impact on the work of researchers in the field. The following section discusses the role of action research within the trends identified in the first section

A Toolkit for Generating Scalable Stochastic Multiobjective Test Problems

Real-world optimization problems typically include uncertainties over various aspects of the problem formulation. Some existing algorithms are designed to cope with stochastic multiobjective optimization problems, but in order to benchmark them, a proper framework still needs to be established. This paper presents a novel toolkit that generates scalable, stochastic, multiobjective optimization problems. A stochastic problem is generated by transforming the objective vectors of a given deterministic test problem into random vectors. All random objective vectors are bounded by the feasible objective space, defined by the deterministic problem. Therefore, the global solution for the deterministic problem can also serve as a reference for the stochastic problem. A simple parametric distribution for the random objective vector is defined in a radial coordinate system, allowing for direct control over the dual challenges of convergence towards the true Pareto front and diversity across the front. An example for a stochastic test problem, generated by the toolkit, is provided

The lessons of policy learning: types, triggers, hindrances and pathologies (article)

This is the author accepted manuscript. The final version is available from Policy Press via the DOI in this record.Policy learning is an attractive proposition, but who learns and for what purposes? Can we learn the wrong lesson? And why do so many attempts to learn what works often fail? In this article, we provide three lessons. First, there are four different modes in which constellations of actors learn. Hence our propositions about learning are conditional on which of the four contexts we refer to. Second, policy learning does not just happen; there are specific hindrances and triggers. Thus, learning can be facilitated by knowing the mechanisms to activate and the likely obstacles. Third, learning itself is a conditional final aim: although the official aspiration of public organizations and politicians is to improve on public policy, policy learning can also be dysfunctional – for an organization, a policy, a constellation of actors or even democracy.The conceptual work was informed by two European Research Council (ERC) projects: Analysis of Learning in Regulatory Governance (ALREG) (grant # 230267) and Procedural Tools for Effective Governance (PROTEGO) (grant # 694632)

Emergency vehicle lane pre-clearing: From microscopic cooperation to routing decision making

Emergency vehicles (EVs) play a crucial role in providing timely help for the general public in saving lives and avoiding property loss. However, very few efforts have been made for EV prioritization on normal road segments, such as the road section between intersections or highways between ramps. In this paper, we propose an EV lane pre-clearing strategy to prioritize EVs on such roads through cooperative driving with surrounding connected vehicles (CVs). The cooperative driving problem is formulated as a mixed-integer nonlinear programming (MINP) problem aiming at (i) guaranteeing the desired speed of EVs, and (ii) minimizing the disturbances on CVs. To tackle this NP-hard MINP problem, we formulate the model in a bi-level optimization manner to address these two objectives, respectively. In the lower-level problem, CVs in front of the emergency vehicle will be divided into several blocks. For each block, we developed an EV sorting algorithm to design optimal merging trajectories for CVs. With resultant sorting trajectories, a constrained optimization problem is solved in the upper-level to determine the initiation time/distance to conduct the sorting trajectories. Case studies show that with the proposed algorithm, emergency vehicles are able to drive at a desired speed while minimizing disturbances on normal traffic flows. We further reveal a linear relationship between the optimal solution and road density, which could help to improve EV routing decision makings when high-resolution data is not available

Reducing critical hindrances to building information modeling implementation: The case of the Singapore construction industry

10.3390/app9183833Applied Sciences (Switzerland)918383

Self-evaluations of selected executive functions in two age group samples

This study assesses the differences between self-evaluations of selected executive functions in two age group samples of both genders. Self-report measures of attention, control, self- esteem, anxiety, self- worth and action style were used to address this aims. This study confirmed that age significantly affects the scores of self-evaluations in almost all the fields of research. In addition, possible perspective of using current battery of measures in future studies is discussed.http://tartu.ester.ee/record=b2647407~S1*es

Search for astro-gravity correlations

A new approach in the gravitational wave experiment is considered. In addition to the old method of searching for coincident reactions of two separated gravitational antennae it was proposed to seek perturbations of the gravitational detector noise background correlated with astrophysical events such as neutrino and gamma ray bursts which can be relaibly registered by correspondent sensors. A general algorithm for this approach is developed. Its efficiency is demonstrated in reanalysis of the old data concerning the phenomenon of neutrino-gravity correlation registered during of SN1987A explosion.Comment: 29 pages (LaTeX), 4 figures (EPS

Robust Peacekeeping? Panacea for Human Rights Violations

This paper examines the conviction that robust peacekeeping—a strong and forceful peacekeeping force—works better than traditional UN peacekeeping mechanisms in reducing human rights violations, specifically, civilian killing, in areas of deployment. I seek to analyze both the operational and internal characteristics of UN peacekeeping operations in an effort to understand the hindrances to achieving the objective of protecting human rights. Specifically, the study examines the contributions of key structural variables, including the mission type, weapon type, rules of engagement, mission strength, and major power participation controlling for other intervening variables using negative binomial and logit regression models. The empirical results indicated that the core variable ―robust peacekeeping‖ has impact on civilian killings, namely that it lowers civilian killings. The key factor seems to be strength of mission size associated with lower numbers of civilian killings. Great power participation, peacekeeper diversity and affinity with the host state, along with identity conflicts and at least proto-democratic status of the host state appear to be harbingers of potentially higher deliberate civilian killing totals. The findings thus have both theoretical and policy implications in the field of peacekeeping