Ecological optimization of an irreversible Brayton cycle with regeneration, inter-cooling and reheating

A mathematical model is developed for an irreversible Brayton cycle with regeneration, inter-cooling and reheating. The irreversibility are from the thermal resistance in the heat exchangers, the pressure drops in pipes, the non-isentropic behavior in the adiabatic expansions and compressions and the heat leakage to the cold source. The cycle is optimized by maximizing the ecological function, which is achieved by the search for optimal values for the temperatures of the cycle and for the pressure ratios of the first stage compression and the first stage expansion. The advantages of using the regenerator, intercooler and reheater are presented by comparison with cycles that do not incorporate one or more of these processes. Optimization results are compared with those obtained by maximizing the power output and it is concluded that the point of maximum ecological function has major advantages with respect to the entropy generation rate and the thermal efficiency, at the cost of a small loss in power.

Proposal of non-invasive experimental model to induce scoliosis in rats

Background: In the literature, there are several experimental models that induce scoliosis in rats; however, they make use of drugs or invasive interventions to generate a scoliotic curve. Objectives: To design and apply a non-invasive immobilization model to induce scoliosis in rats. Methods: Four-week old male Wistar rats (85 +/- 3.3 g) were divided into two groups: control (CG) and scoliosis (SG). The animals in the SG were immobilized by two vests (scapular and pelvic) made from polyvinyl chloride (PVC) and externally attached to each other by a retainer that regulated the scoliosis angle for twelve weeks with left convexity. After immobilization, the abdominal, intercostal, paravertebral, and pectoral muscles were collected for chemical and metabolic analyses. Radiographic reports were performed every 30 days over a 16-week period. Results: The model was effective in the induction of scoliosis, even 30 days after immobilization, with a stable angle of 28 +/- 5 degrees. The chemical and metabolic analyses showed a decrease (p<0.05) in the glycogenic reserves and in the relationship between DNA and total protein reserves of all the muscles analyzed in the scoliosis group, being lower (p<0.05) in the convex side. The values for the Homeostatic Model Assessment of Insulin Resistance indicated a resistance condition to insulin (p<0.05) in the scoliosis group (0.66 +/- 0.03), when compared to the control group (0.81 +/- 0.02). Conclusions: The scoliosis curvature remained stable 30 days after immobilization. The chemical and metabolic analyses suggest changes in muscular homeostasis during the induced scoliosis process.

Generating unconstrained two-dimensional non-guillotine cutting patterns by a Recursive Partitioning Algorithm

In this study, a dynamic programming approach to deal with the unconstrained two-dimensional non-guillotine cutting problem is presented. The method extends the recently introduced recursive partitioning approach for the manufacturer's pallet loading problem. The approach involves two phases and uses bounds based on unconstrained two-staged and non-staged guillotine cutting. The method is able to find the optimal cutting pattern of a large number of pro blem instances of moderate sizes known in the literature and a counterexample for which the approach fails to find known optimal solutions was not found. For the instances that the required computer runtime is excessive, the approach is combined with simple heuristics to reduce its running time. Detailed numerical experiments show the reliability of the method. Journal of the Operational Research Society (2012) 63, 183-200. doi: 10.1057/jors.2011.6 Published online 17 August 2011

New Optimization Algorithms for Structural Reliability Analysis

Solution of structural reliability problems by the First Order method require optimization algorithms to find the smallest distance between a limit state function and the origin of standard Gaussian space. The Hassofer-Lind-Rackwitz-Fiessler (HLRF) algorithm, developed specifically for this purpose, has been shown to be efficient but not robust, as it fails to converge for a significant number of problems. On the other hand, recent developments in general (augmented Lagrangian) optimization techniques have not been tested in aplication to structural reliability problems. In the present article, three new optimization algorithms for structural reliability analysis are presented. One algorithm is based on the HLRF, but uses a new differentiable merit function with Wolfe conditions to select step length in linear search. It is shown in the article that, under certain assumptions, the proposed algorithm generates a sequence that converges to the local minimizer of the problem. Two new augmented Lagrangian methods are also presented, which use quadratic penalties to solve nonlinear problems with equality constraints. Performance and robustness of the new algorithms is compared to the classic augmented Lagrangian method, to HLRF and to the improved HLRF (iHLRF) algorithms, in the solution of 25 benchmark problems from the literature. The new proposed HLRF algorithm is shown to be more robust than HLRF or iHLRF, and as efficient as the iHLRF algorithm. The two augmented Lagrangian methods proposed herein are shown to be more robust and more efficient than the classical augmented Lagrangian method.

A new method for decision making in multi-objective optimization problems

Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-dominated solutions, a Pareto set. Although it is very interesting to know the non-dominated solutions, an additional criterion is needed to select one solution to be deployed. To better support the design process, this paper presents a new method of solving non-linear multi-objective optimization problems by adding a control function that will guide the optimization process over the Pareto set that does not need to be found explicitly. The proposed methodology differs from the classical methods that combine the objective functions in a single scale, and is based on a unique run of non-linear single-objective optimizers.

Design methodology of piezoelectric energy-harvesting skin using topology optimization

Abstract This paper describes a design methodology for piezoelectric energy harvester s that thinly encapsulate the mechanical devices and expl oit resonances from higher- order vibrational modes. The direction of polarization determines the sign of the pi ezoelectric tensor to avoid cancellations of electric fields from opposite polarizations in the same circuit. The resultant modified equations of state are solved by finite element method (FEM). Com- bining this method with the solid isotropic material with penalization (SIMP) method for piezoelectric material, we have developed an optimization methodology that optimizes the piezoelectric material layout and polarization direc- tion. Updating the density function of the SIMP method is performed based on sensitivity analysis, the sequen- tial linear programming on the early stage of the opti- mization, and the phase field method on the latter stage

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.

Performance Optimization of a Floating Breakwater Model Using SPH Method, with a Practical Application

Máster en Oceanografía

Design and synthesis of novel non peptidomimtic beta-secretase inhibitors in the treatment of Alzheimer's disease

The aspartic protease BACE1 (β-amyloid precursor protein cleaving enzyme, β-secretase) is recognized as one of the most promising targets in the treatment of Alzheimer's disease (AD). The accumulation of β-amyloid peptide (Aβ) in the brain is a major factor in the pathogenesis of AD. Aβ is formed by initial cleavage of β-amyloid precursor protein (APP) by β-secretase, therefore BACE1 inhibition represents one of the therapeutic approaches to control progression of AD, by preventing the abnormal generation of Aβ. For this reason, in the last decade, many research efforts have focused at the identification of new BACE1 inhibitors as drug candidates. Generally, BACE1 inhibitors are grouped into two families: substrate-based inhibitors, designed as peptidomimetic inhibitors, and non-peptidomimetic ones. The research on non-peptidomimetic small molecules BACE1 inhibitors remains the most interesting approach, since these compounds hold an improved bioavailability after systemic administration, due to a good blood-brain barrier permeability in comparison to peptidomimetic inhibitors. Very recently, our research group discovered a new promising lead compound for the treatment of AD, named lipocrine, a hybrid derivative between lipoic acid and the AChE inhibitor (AChEI) tacrine, characterized by a tetrahydroacridinic moiety. Lipocrine is one of the first compounds able to inhibit the catalytic activity of AChE and AChE-induced amyloid-β aggregation and to protect against reactive oxygen species. Due to this interesting profile, lipocrine was also evaluated for BACE1 inhibitory activity, resulting in a potent lead compound for BACE1 inhibition. Starting from this interesting profile, a series of tetrahydroacridine analogues were synthesised varying the chain length between the two fragments. Moreover, following the approach of combining in a single molecule two different pharmacophores, we designed and synthesised different compounds bearing the moieties of known AChEIs (rivastigmine and caproctamine) coupled with lipoic acid, since it was shown that dithiolane group is an important structural feature of lipocrine for the optimal inhibition of BACE1. All the tetrahydroacridines, rivastigmine and caproctamine-based compounds, were evaluated for BACE1 inhibitory activity in a FRET (fluorescence resonance energy transfer) enzymatic assay (test A). With the aim to enhancing the biological activity of the lead compound, we applied the molecular simplification approach to design and synthesize novel heterocyclic compounds related to lipocrine, in which the tetrahydroacridine moiety was replaced by 4-amino-quinoline or 4-amino-quinazoline rings. All the synthesized compounds were also evaluated in a modified FRET enzymatic assay (test B), changing the fluorescent substrate for enzymatic BACE1 cleavage. This test method guided deep structure-activity relationships for BACE1 inhibition on the most promising quinazoline-based derivatives. By varying the substituent on the 2-position of the quinazoline ring and by replacing the lipoic acid residue in lateral chain with different moieties (i.e. trans-ferulic acid, a known antioxidant molecule), a series of quinazoline derivatives were obtained. In order to confirm inhibitory activity of the most active compounds, they were evaluated with a third FRET assay (test C) which, surprisingly, did not confirm the previous good activity profiles. An evaluation study of kinetic parameters of the three assays revealed that method C is endowed with the best specificity and enzymatic efficiency. Biological evaluation of the modified 2,4-diamino-quinazoline derivatives measured through the method C, allow to obtain a new lead compound bearing the trans-ferulic acid residue coupled to 2,4-diamino-quinazoline core endowed with a good BACE1 inhibitory activity (IC50 = 0.8 mM). We reported on the variability of the results in the three different FRET assays that are known to have some disadvantages in term of interference rates that are strongly dependent on compound properties. The observed results variability could be also ascribed to different enzyme origin, varied substrate and different fluorescent groups. The inhibitors should be tested on a parallel screening in order to have a more reliable data prior to be tested into cellular assay. With this aim, preliminary cellular BACE1 inhibition assay carried out on lipocrine confirmed a good cellular activity profile (EC50 = 3.7 mM) strengthening the idea to find a small molecule non-peptidomimetic compound as BACE1 inhibitor. In conclusion, the present study allowed to identify a new lead compound endowed with BACE1 inhibitory activity in submicromolar range. Further lead optimization to the obtained derivative is needed in order to obtain a more potent and a selective BACE1 inhibitor based on 2,4-diamino-quinazoline scaffold. A side project related to the synthesis of novel enzymatic inhibitors of BACE1 in order to explore the pseudopeptidic transition-state isosteres chemistry was carried out during research stage at Università de Montrèal (Canada) in Hanessian's group. The aim of this work has been the synthesis of the δ-aminocyclohexane carboxylic acid motif with stereochemically defined substitution to incorporating such a constrained core in potential BACE1 inhibitors. This fragment, endowed with reduced peptidic character, is not known in the context of peptidomimetic design. In particular, we envisioned an alternative route based on an organocatalytic asymmetric conjugate addition of nitroalkanes to cyclohexenone in presence of D-proline and trans-2,5-dimethylpiperazine. The enantioenriched obtained 3-(α-nitroalkyl)-cyclohexanones were further functionalized to give the corresponding δ-nitroalkyl cyclohexane carboxylic acids. These intermediates were elaborated to the target structures 3-(α-aminoalkyl)-1-cyclohexane carboxylic acids in a new readily accessible way.

Second law analysis and simulation techniques for the energy optimization of buildings

The research activity described in this thesis is focused mainly on the study of finite-element techniques applied to thermo-fluid dynamic problems of plant components and on the study of dynamic simulation techniques applied to integrated building design in order to enhance the energy performance of the building. The first part of this doctorate thesis is a broad dissertation on second law analysis of thermodynamic processes with the purpose of including the issue of the energy efficiency of buildings within a wider cultural context which is usually not considered by professionals in the energy sector. In particular, the first chapter includes, a rigorous scheme for the deduction of the expressions for molar exergy and molar flow exergy of pure chemical fuels. The study shows that molar exergy and molar flow exergy coincide when the temperature and pressure of the fuel are equal to those of the environment in which the combustion reaction takes place. A simple method to determine the Gibbs free energy for non-standard values of the temperature and pressure of the environment is then clarified. For hydrogen, carbon dioxide, and several hydrocarbons, the dependence of the molar exergy on the temperature and relative humidity of the environment is reported, together with an evaluation of molar exergy and molar flow exergy when the temperature and pressure of the fuel are different from those of the environment. As an application of second law analysis, a comparison of the thermodynamic efficiency of a condensing boiler and of a heat pump is also reported. The second chapter presents a study of borehole heat exchangers, that is, a polyethylene piping network buried in the soil which allows a ground-coupled heat pump to exchange heat with the ground. After a brief overview of low-enthalpy geothermal plants, an apparatus designed and assembled by the author to carry out thermal response tests is presented. Data obtained by means of in situ thermal response tests are reported and evaluated by means of a finite-element simulation method, implemented through the software package COMSOL Multyphysics. The simulation method allows the determination of the precise value of the effective thermal properties of the ground and of the grout, which are essential for the design of borehole heat exchangers. In addition to the study of a single plant component, namely the borehole heat exchanger, in the third chapter is presented a thorough process for the plant design of a zero carbon building complex. The plant is composed of: 1) a ground-coupled heat pump system for space heating and cooling, with electricity supplied by photovoltaic solar collectors; 2) air dehumidifiers; 3) thermal solar collectors to match 70% of domestic hot water energy use, and a wood pellet boiler for the remaining domestic hot water energy use and for exceptional winter peaks. This chapter includes the design methodology adopted: 1) dynamic simulation of the building complex with the software package TRNSYS for evaluating the energy requirements of the building complex; 2) ground-coupled heat pumps modelled by means of TRNSYS; and 3) evaluation of the total length of the borehole heat exchanger by an iterative method developed by the author. An economic feasibility and an exergy analysis of the proposed plant, compared with two other plants, are reported. The exergy analysis was performed by considering the embodied energy of the components of each plant and the exergy loss during the functioning of the plants.

Design and optimization of components and processes for plasma sources in advanced material treatments

The research activities described in the present thesis have been oriented to the design and development of components and technological processes aimed at optimizing the performance of plasma sources in advanced in material treatments. Consumables components for high definition plasma arc cutting (PAC) torches were studied and developed. Experimental activities have in particular focussed on the modifications of the emissive insert with respect to the standard electrode configuration, which comprises a press fit hafnium insert in a copper body holder, to improve its durability. Based on a deep analysis of both the scientific and patent literature, different solutions were proposed and tested. First, the behaviour of Hf cathodes when operating at high current levels (250A) in oxidizing atmosphere has been experimentally investigated optimizing, with respect to expected service life, the initial shape of the electrode emissive surface. Moreover, the microstructural modifications of the Hf insert in PAC electrodes were experimentally investigated during first cycles, in order to understand those phenomena occurring on and under the Hf emissive surface and involved in the electrode erosion process. Thereafter, the research activity focussed on producing, characterizing and testing prototypes of composite inserts, combining powders of a high thermal conductibility (Cu, Ag) and high thermionic emissivity (Hf, Zr) materials The complexity of the thermal plasma torch environment required and integrated approach also involving physical modelling. Accordingly, a detailed line-by-line method was developed to compute the net emission coefficient of Ar plasmas at temperatures ranging from 3000 K to 25000 K and pressure ranging from 50 kPa to 200 kPa, for optically thin and partially autoabsorbed plasmas. Finally, prototypal electrodes were studied and realized for a newly developed plasma source, based on the plasma needle concept and devoted to the generation of atmospheric pressure non-thermal plasmas for biomedical applications.

Integrated analysis and design of optimization and up-scaling of inductively coupled plasma synthesis of nanoparticles

This study is focused on radio-frequency inductively coupled thermal plasma (ICP) synthesis of nanoparticles, combining experimental and modelling approaches towards process optimization and industrial scale-up, in the framework of the FP7-NMP SIMBA European project (Scaling-up of ICP technology for continuous production of Metallic nanopowders for Battery Applications). First the state of the art of nanoparticle production through conventional and plasma routes is summarized, then results for the characterization of the plasma source and on the investigation of the nanoparticle synthesis phenomenon, aiming at highlighting fundamental process parameters while adopting a design oriented modelling approach, are presented. In particular, an energy balance of the torch and of the reaction chamber, employing a calorimetric method, is presented, while results for three- and two-dimensional modelling of an ICP system are compared with calorimetric and enthalpy probe measurements to validate the temperature field predicted by the model and used to characterize the ICP system under powder-free conditions. Moreover, results from the modeling of critical phases of ICP synthesis process, such as precursor evaporation, vapour conversion in nanoparticles and nanoparticle growth, are presented, with the aim of providing useful insights both for the design and optimization of the process and on the underlying physical phenomena. Indeed, precursor evaporation, one of the phases holding the highest impact on industrial feasibility of the process, is discussed; by employing models to describe particle trajectories and thermal histories, adapted from the ones originally developed for other plasma technologies or applications, such as DC non-transferred arc torches and powder spherodization, the evaporation of micro-sized Si solid precursor in a laboratory scale ICP system is investigated. Finally, a discussion on the role of thermo-fluid dynamic fields on nano-particle formation is presented, as well as a study on the effect of the reaction chamber geometry on produced nanoparticle characteristics and process yield.

Temperature Variation Aware Energy Optimization in Heterogeneous MPSoCs

Thermal effects are rapidly gaining importance in nanometer heterogeneous integrated systems. Increased power density, coupled with spatio-temporal variability of chip workload, cause lateral and vertical temperature non-uniformities (variations) in the chip structure. The assumption of an uniform temperature for a large circuit leads to inaccurate determination of key design parameters. To improve design quality, we need precise estimation of temperature at detailed spatial resolution which is very computationally intensive. Consequently, thermal analysis of the designs needs to be done at multiple levels of granularity. To further investigate the flow of chip/package thermal analysis we exploit the Intel Single Chip Cloud Computer (SCC) and propose a methodology for calibration of SCC on-die temperature sensors. We also develop an infrastructure for online monitoring of SCC temperature sensor readings and SCC power consumption. Having the thermal simulation tool in hand, we propose MiMAPT, an approach for analyzing delay, power and temperature in digital integrated circuits. MiMAPT integrates seamlessly into industrial Front-end and Back-end chip design flows. It accounts for temperature non-uniformities and self-heating while performing analysis. Furthermore, we extend the temperature variation aware analysis of designs to 3D MPSoCs with Wide-I/O DRAM. We improve the DRAM refresh power by considering the lateral and vertical temperature variations in the 3D structure and adapting the per-DRAM-bank refresh period accordingly. We develop an advanced virtual platform which models the performance, power, and thermal behavior of a 3D-integrated MPSoC with Wide-I/O DRAMs in detail. Moving towards real-world multi-core heterogeneous SoC designs, a reconfigurable heterogeneous platform (ZYNQ) is exploited to further study the performance and energy efficiency of various CPU-accelerator data sharing methods in heterogeneous hardware architectures. A complete hardware accelerator featuring clusters of OpenRISC CPUs, with dynamic address remapping capability is built and verified on a real hardware.

Packing a trunk : a physically based approach with full motional freedom

Geometric packing problems may be formulated mathematically as constrained optimization problems. But finding a good solution is a challenging task. The more complicated the geometry of the container or the objects to be packed, the more complex the non-penetration constraints become. In this work we propose the use of a physics engine that simulates a system of colliding rigid bodies. It is a tool to resolve interpenetration conflicts and to optimize configurations locally. We develop an efficient and easy-to-implement physics engine that is specialized for collision detection and contact handling. In succession of the development of this engine a number of novel algorithms for distance calculation and intersection volume were designed and imple- mented, which are presented in this work. They are highly specialized to pro- vide fast responses for cuboids and triangles as input geometry whereas the concepts they are based on can easily be extended to other convex shapes. Especially noteworthy in this context is our ε-distance algorithm - a novel application that is not only very robust and fast but also compact in its im- plementation. Several state-of-the-art third party implementations are being presented and we show that our implementations beat them in runtime and robustness. The packing algorithm that lies on top of the physics engine is a Monte Carlo based approach implemented for packing cuboids into a container described by a triangle soup. We give an implementation for the SAE J1100 variant of the trunk packing problem. We compare this implementation to several established approaches and we show that it gives better results in faster time than these existing implementations.

Optimization of RNA-based transgene expression by targeting Protein Kinase R

The aim of this thesis was to establish a method for repeated transfection of in vitro transcribed RNA (IVT-RNA) leading to a sustained protein expression lasting for days or even weeks. Once transfected cells recognize IVT-RNA as "non-self" and initiate defense pathways leading to an upregulated interferon (IFN) response and stalled translation. In this work Protein Kinase R (PKR) was identified as the main effector molecule mediating this cellular response. We assessed four strategies to inhibit PKR and the IFN response: A small molecule PKR inhibitor enhanced protein expression and hampered the induction of IFN-transcripts, but had to be excluded due to cytotoxicity. A siRNA mediated PKR knockdown and the overexpression of a kinase inactive PKR mutant elevated the protein expression, but the down-regulation of the IFN response was insufficient. The co-transfer of the viral inhibitors of PKR and the IFN response was most successful. The use of E3, K3 and B18R co-transfection enabled repeated IVT-RNA-based transfection of human fibroblasts. Thus, the developed protocol allows a continuous IVT-RNA encoded protein expression of proteins, which could be the basis for the generation of induced pluripotent stem cells (iPS) for several therapeutic applications in regenerative medicine or drug research.