Modern optimization in earthwork construction

Earthworks tasks are often regarded in transportation projects as some of the most demanding processes. In fact, sequential tasks such as excavation, transportation, spreading and compaction are strongly based on heavy mechanical equipment and repetitive processes, thus becoming as economically demanding as they are time-consuming. Moreover, actual construction requirements originate higher demands for productivity and safety in earthwork constructions. Given the percentual weight of costs and duration of earthworks in infrastructure construction, the optimal usage of every resource in these tasks is paramount. Considering the characteristics of an earthwork construction, it can be looked at as a production line based on resources (mechanical equipment) and dependency relations between sequential tasks, hence being susceptible to optimization. Up to the present, the steady development of Information Technology areas, such as databases, artificial intelligence and operations research, has resulted in the emergence of several technologies with potential application bearing that purpose in mind. Among these, modern optimization methods (also known as metaheuristics), such as evolutionary computation, have the potential to find high quality optimal solutions with a reasonable use of computational resources. In this context, this work describes an optimization algorithm for earthworks equipment allocation based on a modern optimization approach, which takes advantage of the concept that an earthwork construction can be regarded as a production line.

Earthwork optimization system for sustainable highway construction

In highway construction, earthworks refer to the tasks of excavation, transportation, spreading and compaction of geomaterial (e.g. soil, rockfill and soil-rockfill mixture). Whereas relying heavily on machinery and repetitive processes, these tasks are highly susceptible to optimization. In this context Artificial Intelligent techniques, such as Data Mining and modern optimization can be applied for earthworks. A survey of these applications shows that they focus on the optimization of specific objectives and/or construction phases being possible to identify the capabilities and limitations of the analyzed techniques. Thus, according to the pinpointed drawbacks of these techniques, this paper describes a novel intelligent earthwork optimization system, capable of integrating DM, modern optimization and GIS technologies in order to optimize the earthwork processes throughout all phases of design and construction work. This integration system allows significant savings in time, cost and gas emissions contributing for a more sustainable construction.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Floristic, edaphic and structural characteristics of flooded and unflooded forests in the lower Rio Purús region of central Amazonia, Brazil

Despite a natural history interest in the early 1900s, relatively little ecological research has been carried out in the Rio Purús basin of central Amazonia, Brazil. Here we describe a new study area in the region of Lago Uauaçú with an emphasis on the climate, forest structure and composition, and soil characteristics between adjacent unflooded (terra firme) and seasonally inundated forests; situated within both the white-water (várzea) and black-water (igapó) drainage systems that dominate the landscape. The climate was found to be typical of that of the central Amazon. Várzea forest soils had high concentrations of nutrients, while terra firme and igapó soils were comparatively nutrient-poor. Terra firme forests were the most floristically diverse forest type, whereas várzea was intermediate, and igapó the most species-poor. The Lecythidaceae was the most important family in terra firme while the Euphorbiaceae was the most important in both várzea and igapó. There were significant differences between forest types in terms of number of saplings, canopy cover and understorey density. In contrasting our results with other published information, we conclude that the Lago Uauaçú region consists of a typical central Amazonian forest macro-mosaic, but is a unique area with high conservation value due to the intimate juxtaposition of terra firme, várzea and igapó forests.

Design and optimization of an extrusion die for the production of wood–plastic composite profiles

In this work, the optimization of an extrusion die designed for the production of a wood–plastic composite (WPC) decking profile is investigated. The optimization was performed with the help of numerical tools, more precisely, by solving the continuity and momentum conservation equations that govern such flow, and aiming to balance properly the flow distribution at the extrusion die flow channel outlet. To capture the rheological behavior of the material, we used a Bird-Carreau model with parameters obtained from a fit to the (shear viscosity versus shearrate) experimental data, collected from rheological tests. To yield a balanced output flow, several numerical runs were performed by adjusting the flow restriction at different regions of the flow-channel parallel zone crosssection. The simulations were compared with the experimental results and an excellent qualitative agreement was obtained, allowing, in this way, to attain a good balancing of the output flow and emphasizing the advantages of using numerical tools to aid the design of profile extrusion dies.

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

Structural, optical and magnetic properties of pulsed laser deposited Co-doped ZnO films

Zn1−xCoxO films with different Co concentrations (with x=0.00, 0.10, 0.15, and 0.30) were grown by pulsed laser deposition (PLD) technique. The structural and optical properties of the films were investigated by grazing incidence X-ray diffraction (GIXRD), Raman spectroscopy and photoluminescence (PL). The magnetic properties were measured by conventional magnetometry using a SQUID and simulated by ab-initio calculations using Korring–Khon–Rostoker (KKR) method combined with coherent potential approximation (CPA). The effect of Co-doping on the GIXRD and Raman peaks positions, shape and intensity is discussed. PL studies demonstrate that Co-doping induces a decrease of the bandgap energy and quenching of the UV emission. They also suggest the presence of Zn interstitials when x≥0.15. The 10% Co-doped ZnO film shows ferromagnetism at 390 K with a spontaneous magnetic moment ≈4×10−5 emu and coercive field ≈0.17 kOe. The origin of ferromagnetism is explained based on the calculations using KKR method.

Structural, mechanical and piezoelectric properties of polycrystalline AlN films sputtered on titanium bottom electrodes

Polycrystalline AlN coatings deposited on Ti-electrodes films were sputtered by using nitrogen both as reactive gas and sputtering gas, in order to obtain high purity coatings with appropriate properties to be further integrated into wear resistance coatings as a piezoelectric monitoring wear sensor. The chemical composition, the structure and the morphology of the films were investigated by X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy and atomic force microscopy techniques. These measurements show the formation of highly (101), (102) and (103) oriented AlN films with good piezoelectric and mechanical properties suitable for applications in electronic devices. Through the use of lower nitrogen flow a densification of the AlN coating occurs in the microstructure, with an improvement of the crystallinity along with the increase of the hardness. Thermal stability of aluminum nitride coatings at high temperature was also examined. It was found an improvement of the piezoelectric properties of the highly (10x) oriented AlN films which became c-axis (002) oriented after annealing. The mechanical behavior after heat treatment shows an important enhancement of the surface hardness and Young’s modulus, which decrease rapidly with the increase of the indentation depth until approach constant values close to the substrate properties after annealing. Thus, thermal annealing energy promotes not only the rearrangement of Al–N network, but also the occurrence of a nitriding process of unsaturated Al atoms which cause a surface hardening of the film.

Cost-effective energy and carbon emission optimization in building renovation – A case-study in a low income neighbourhood

Construction sector is one of the major responsible for energy consumption and carbon emissions and renovation of existing buildings plays an important role in the actions to mitigate climate changes. Present work is based on the methodology developed in IEA Annex 56, allowing identifying cost optimal and cost effective renovation scenarios improving the energy performance. The analysed case study is a residential neighbourhood of the municipality of Gaia in Portugal. The analysis compares a reference renovation scenario (without improving the energy performance of the building) with a series of alternative renovation scenarios, including the one that is being implemented.

IEA EBC Annex56 vision for cost effective energy and carbon emissions optimization in building renovation

Building sector has become an important target for carbon emissions reduction, energy consumption and resources depletion. Due to low rates of replacement of the existing buildings, their low energy performances are a major concern. Most of the current regulations are focused on new buildings and do not account with the several technical, functional and economic constraints that have to be faced in the renovation of existing buildings. Thus, a new methodology is proposed to be used in the decision making process for energy related building renovation, allowing finding a cost-effective balance between energy consumption, carbon emissions and overall added value.

Towards high performance and multi-functional structural membranes using advanced fibrous and textile materials

Scientific and technological advancements in the area of fibrous and textile materials have greatly enhanced their application potential in several high-end technical and industrial sectors including construction, transportation, medical, sports, aerospace engineering, electronics and so on. Excellent performance accompanied by light-weight, mechanical flexibility, tailor-ability, design flexibility, easy fabrication and relatively lower cost are the driving forces towards wide applications of these materials. Cost-effective fabrication of various advanced and functional materials for structural parts, medical devices, sensors, energy harvesting devices, capacitors, batteries, and many others has been possible using fibrous and textile materials. Structural membranes are one of the innovative applications of textile structures and these novel building skins are becoming very popular due to flexible design aesthetics, durability, lightweight and cost benefits. Current demand on high performance and multi-functional materials in structural applications has motivated to go beyond the basic textile structures used for structural membranes and to use innovative textile materials. Structural membranes with self-cleaning, thermoregulation and energy harvesting capability (using solar cells) are examples of such recently developed multi-functional membranes. Besides these, there exist enormous opportunities to develop wide varieties of multi-functional membranes using functional textile materials. Additionally, it is also possible to further enhance the performance and functionalities of structural membranes using advanced fibrous architectures such as 2D, 3D, hybrid, multi-layer and so on. In this context, the present paper gives an overview of various advanced and functional fibrous and textile materials which have enormous application potential in structural membranes.

Global vs. local nonlinear optimization techniques for human-like movement of an anthropomorphic robot

In this paper a comparison between using global and local optimization techniques for solving the problem of generating human-like arm and hand movements for an anthropomorphic dual arm robot is made. Although the objective function involved in each optimization problem is convex, there is no evidence that the admissible regions of these problems are convex sets. For the sequence of movements for which the numerical tests were done there were no significant differences between the optimal solutions obtained using the global and the local techniques. This suggests that the optimal solution obtained using the local solver is indeed a global solution.

Nonlinear optimization for human-like synchronous movements of a dual arm-hand robotic system

In previous work we have presented a model capable of generating human-like movements for a dual arm-hand robot involved in human-robot cooperative tasks. However, the focus was on the generation of reach-to-grasp and reach-to-regrasp bimanual movements and no synchrony in timing was taken into account. In this paper we extend the previous model in order to accomplish bimanual manipulation tasks by synchronously moving both arms and hands of an anthropomorphic robotic system. Specifically, the new extended model has been designed for two different tasks with different degrees of difficulty. Numerical results were obtained by the implementation of the IPOPT solver embedded in our MATLAB simulator.

Towards human-like bimanual movements in anthropomorphic robots: a nonlinear optimization approach

Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.