Generalized Differential Quadrature Finite Element Method applied to Advanced Structural Mechanics

Over the years the Differential Quadrature (DQ) method has distinguished because of its high accuracy, straightforward implementation and general ap- plication to a variety of problems. There has been an increase in this topic by several researchers who experienced significant development in the last years. DQ is essentially a generalization of the popular Gaussian Quadrature (GQ) used for numerical integration functions. GQ approximates a finite in- tegral as a weighted sum of integrand values at selected points in a problem domain whereas DQ approximate the derivatives of a smooth function at a point as a weighted sum of function values at selected nodes. A direct appli- cation of this elegant methodology is to solve ordinary and partial differential equations. Furthermore in recent years the DQ formulation has been gener- alized in the weighting coefficients computations to let the approach to be more flexible and accurate. As a result it has been indicated as Generalized Differential Quadrature (GDQ) method. However the applicability of GDQ in its original form is still limited. It has been proven to fail for problems with strong material discontinuities as well as problems involving singularities and irregularities. On the other hand the very well-known Finite Element (FE) method could overcome these issues because it subdivides the computational domain into a certain number of elements in which the solution is calculated. Recently, some researchers have been studying a numerical technique which could use the advantages of the GDQ method and the advantages of FE method. This methodology has got different names among each research group, it will be indicated here as Generalized Differential Quadrature Finite Element Method (GDQFEM).

Design and optimization of turbo-expanders for organic rankine cycles

In a world focused on the need to produce energy for a growing population, while reducing atmospheric emissions of carbon dioxide, organic Rankine cycles represent a solution to fulfil this goal. This study focuses on the design and optimization of axial-flow turbines for organic Rankine cycles. From the turbine designer point of view, most of this fluids exhibit some peculiar characteristics, such as small enthalpy drop, low speed of sound, large expansion ratio. A computational model for the prediction of axial-flow turbine performance is developed and validated against experimental data. The model allows to calculate turbine performance within a range of accuracy of ±3%. The design procedure is coupled with an optimization process, performed using a genetic algorithm where the turbine total-to-static efficiency represents the objective function. The computational model is integrated in a wider analysis of thermodynamic cycle units, by providing the turbine optimal design. First, the calculation routine is applied in the context of the Draugen offshore platform, where three heat recovery systems are compared. The turbine performance is investigated for three competing bottoming cycles: organic Rankine cycle (operating cyclopentane), steam Rankine cycle and air bottoming cycle. Findings indicate the air turbine as the most efficient solution (total-to-static efficiency = 0.89), while the cyclopentane turbine results as the most flexible and compact technology (2.45 ton/MW and 0.63 m3/MW). Furthermore, the study shows that, for organic and steam Rankine cycles, the optimal design configurations for the expanders do not coincide with those of the thermodynamic cycles. This suggests the possibility to obtain a more accurate analysis by including the computational model in the simulations of the thermodynamic cycles. Afterwards, the performance analysis is carried out by comparing three organic fluids: cyclopentane, MDM and R245fa. Results suggest MDM as the most effective fluid from the turbine performance viewpoint (total-to-total efficiency = 0.89). On the other hand, cyclopentane guarantees a greater net power output of the organic Rankine cycle (P = 5.35 MW), while R245fa represents the most compact solution (1.63 ton/MW and 0.20 m3/MW). Finally, the influence of the composition of an isopentane/isobutane mixture on both the thermodynamic cycle performance and the expander isentropic efficiency is investigated. Findings show how the mixture composition affects the turbine efficiency and so the cycle performance. Moreover, the analysis demonstrates that the use of binary mixtures leads to an enhancement of the thermodynamic cycle performance.

Stima dei parametri di modelli idrologici mediante ottimizzazione dell’utilità

Tradizionalmente, l'obiettivo della calibrazione di un modello afflussi-deflussi è sempre stato quello di ottenere un set di parametri (o una distribuzione di probabilità dei parametri) che massimizzasse l'adattamento dei dati simulati alla realtà osservata, trattando parzialmente le finalità applicative del modello. Nel lavoro di tesi viene proposta una metodologia di calibrazione che trae spunto dell'evidenza che non sempre la corrispondenza tra dati osservati e simulati rappresenti il criterio più appropriato per calibrare un modello idrologico. Ai fini applicativi infatti, può risultare maggiormente utile una miglior rappresentazione di un determinato aspetto dell'idrogramma piuttosto che un altro. Il metodo di calibrazione che viene proposto mira a valutare le prestazioni del modello stimandone l'utilità nell'applicazione prevista. Tramite l'utilizzo di opportune funzioni, ad ogni passo temporale viene valutata l'utilità della simulazione ottenuta. La calibrazione viene quindi eseguita attraverso la massimizzazione di una funzione obiettivo costituita dalla somma delle utilità stimate nei singoli passi temporali. Le analisi mostrano come attraverso l'impiego di tali funzioni obiettivo sia possibile migliorare le prestazioni del modello laddove ritenute di maggior interesse per per le finalità applicative previste.

Compensation, Incentives and Risk: Economic Theory and Russian Practise

Mr. Pechersky set out to examine a specific feature of the employer-employee relationship in Russian business organisations. He wanted to study to what extent the so-called "moral hazard" is being solved (if it is being solved at all), whether there is a relationship between pay and performance, and whether there is a correlation between economic theory and Russian reality. Finally, he set out to construct a model of the Russian economy that better reflects the way it actually functions than do certain other well-known models (for example models of incentive compensation, the Shapiro-Stiglitz model etc.). His report was presented to the RSS in the form of a series of manuscripts in English and Russian, and on disc, with many tables and graphs. He begins by pointing out the different examples of randomness that exist in the relationship between employee and employer. Firstly, results are frequently affected by circumstances outside the employee's control that have nothing to do with how intelligently, honestly, and diligently the employee has worked. When rewards are based on results, uncontrollable randomness in the employee's output induces randomness in their incomes. A second source of randomness involves the outside events that are beyond the control of the employee that may affect his or her ability to perform as contracted. A third source of randomness arises when the performance itself (rather than the result) is measured, and the performance evaluation procedures include random or subjective elements. Mr. Pechersky's study shows that in Russia the third source of randomness plays an important role. Moreover, he points out that employer-employee relationships in Russia are sometimes opposite to those in the West. Drawing on game theory, he characterises the Western system as follows. The two players are the principal and the agent, who are usually representative individuals. The principal hires an agent to perform a task, and the agent acquires an information advantage concerning his actions or the outside world at some point in the game, i.e. it is assumed that the employee is better informed. In Russia, on the other hand, incentive contracts are typically negotiated in situations in which the employer has the information advantage concerning outcome. Mr. Pechersky schematises it thus. Compensation (the wage) is W and consists of a base amount, plus a portion that varies with the outcome, x. So W = a + bx, where b is used to measure the intensity of the incentives provided to the employee. This means that one contract will be said to provide stronger incentives than another if it specifies a higher value for b. This is the incentive contract as it operates in the West. The key feature distinguishing the Russian example is that x is observed by the employer but is not observed by the employee. So the employer promises to pay in accordance with an incentive scheme, but since the outcome is not observable by the employee the contract cannot be enforced, and the question arises: is there any incentive for the employer to fulfil his or her promises? Mr. Pechersky considers two simple models of employer-employee relationships displaying the above type of information symmetry. In a static framework the obtained result is somewhat surprising: at the Nash equilibrium the employer pays nothing, even though his objective function contains a quadratic term reflecting negative consequences for the employer if the actual level of compensation deviates from the expectations of the employee. This can lead, for example, to labour turnover, or the expenses resulting from a bad reputation. In a dynamic framework, the conclusion can be formulated as follows: the higher the discount factor, the higher the incentive for the employer to be honest in his/her relationships with the employee. If the discount factor is taken to be a parameter reflecting the degree of (un)certainty (the higher the degree of uncertainty is, the lower is the discount factor), we can conclude that the answer to the formulated question depends on the stability of the political, social and economic situation in a country. Mr. Pechersky believes that the strength of a market system with private property lies not just in its providing the information needed to compute an efficient allocation of resources in an efficient manner. At least equally important is the manner in which it accepts individually self-interested behaviour, but then channels this behaviour in desired directions. People do not have to be cajoled, artificially induced, or forced to do their parts in a well-functioning market system. Instead, they are simply left to pursue their own objectives as they see fit. Under the right circumstances, people are led by Adam Smith's "invisible hand" of impersonal market forces to take the actions needed to achieve an efficient, co-ordinated pattern of choices. The problem is that, as Mr. Pechersky sees it, there is no reason to believe that the circumstances in Russia are right, and the invisible hand is doing its work properly. Political instability, social tension and other circumstances prevent it from doing so. Mr. Pechersky believes that the discount factor plays a crucial role in employer-employee relationships. Such relationships can be considered satisfactory from a normative point of view, only in those cases where the discount factor is sufficiently large. Unfortunately, in modern Russia the evidence points to the typical discount factor being relatively small. This fact can be explained as a manifestation of aversion to risk of economic agents. Mr. Pechersky hopes that when political stabilisation occurs, the discount factors of economic agents will increase, and the agent's behaviour will be explicable in terms of more traditional models.

Efficacy and safety of intravenous meropenem and tobramycin versus ceftazidime and tobramycin in cystic fibrosis

BACKGROUND: Cystic fibrosis (CF) is characterized by chronic bacterial broncho-pulmonary infection. Although intravenous (IV) antibiotic therapy is regarded as standard treatment in CF, only few randomised trials comparing different antibiotic compounds exist. METHODS: We report on a prospective multicenter interventional trial of IV meropenem (120 mg/kg/day) or IV ceftazidime (200-400 mg/kg/day), each administered together with IV tobramycin (9-12 mg/kg/day). Outcome measures were changes in lung function, microbiological sputum burden and blood inflammatory marker. Liver and renal function values were measured to assess safety. RESULTS: One hundred eighteen patients (59/59) were included into the study with the following indications: first infection of P. aeruginosa (n=6), acute pulmonary exacerbation (n=34) and suppression therapy of chronic P. aeruginosa colonization (n=78). Both treatments improved lung function measures, bacterial sputum burden and CRP levels with no differences between treatment groups observed. A significant higher elevation for alkaline phosphatase (p<0.0001) was observed for patients in the meropenem/tobramycin group. CONCLUSIONS: IV antibiotic therapy in CF patients with meropenem/tobramycin is as effective as with ceftazidime/tobramycin regarding lung function, microbiological sputum burden and systemic inflammatory status. Hepato-biliary function should be monitored carefully during IV treatment, possibly important in CF patients with pre-existing liver disease.

Fully automatic X-ray image segmentation via joint estimation of image displacements.

We propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. Our algorithm works by estimating the displacements from image patches to the (unknown) landmark positions and then integrating them via voting. The fundamental contribution is that, we jointly estimate the displacements from all patches to multiple landmarks together, by considering not only the training data but also geometric constraints on the test image. The various constraints constitute a convex objective function that can be solved efficiently. Validated on three challenging datasets, our method achieves high accuracy in landmark detection, and, combined with statistical shape model, gives a better performance in shape segmentation compared to the state-of-the-art methods.

Scheduling the factory pick-up of new cars

Car manufacturers increasingly offer delivery programs for the factory pick-up of new cars. Such a program consists of a broad range of event-marketing activities. In this paper we investigate the problem of scheduling the delivery program activities of one day such that the sum of the customers’ waiting times is minimized. We show how to model this problem as a resource-constrained project scheduling problem with nonregular objective function, and we present a relaxation-based beam-search solution heuristic. The relaxations are solved by exploiting a duality relationship between temporal scheduling and min-cost network flow problems. This approach has been developed in cooperation with a German automaker. The performance of the heuristic has been evaluated based on practical and randomly generated test instances.

Advanced production scheduling for batch plants in process industries

An Advanced Planning System (APS) offers support at all planning levels along the supply chain while observing limited resources. We consider an APS for process industries (e.g. chemical and pharmaceutical industries) consisting of the modules network design (for long–term decisions), supply network planning (for medium–term decisions), and detailed production scheduling (for short–term decisions). For each module, we outline the decision problem, discuss the specifi cs of process industries, and review state–of–the–art solution approaches. For the module detailed production scheduling, a new solution approach is proposed in the case of batch production, which can solve much larger practical problems than the methods known thus far. The new approach decomposes detailed production scheduling for batch production into batching and batch scheduling. The batching problem converts the primary requirements for products into individual batches, where the work load is to be minimized. We formulate the batching problem as a nonlinear mixed–integer program and transform it into a linear mixed–binary program of moderate size, which can be solved by standard software. The batch scheduling problem allocates the batches to scarce resources such as processing units, workers, and intermediate storage facilities, where some regular objective function like the makespan is to be minimized. The batch scheduling problem is modelled as a resource–constrained project scheduling problem, which can be solved by an efficient truncated branch–and–bound algorithm developed recently. The performance of the new solution procedures for batching and batch scheduling is demonstrated by solving several instances of a case study from process industries.

Patient classification system: An integrated method for measuring nursing intensity and optimizing resource allocation

A patient classification system was developed integrating a patient acuity instrument with a computerized nursing distribution method based on a linear programming model. The system was designed for real-time measurement of patient acuity (workload) and allocation of nursing personnel to optimize the utilization of resources.^ The acuity instrument was a prototype tool with eight categories of patients defined by patient severity and nursing intensity parameters. From this tool, the demand for nursing care was defined in patient points with one point equal to one hour of RN time. Validity and reliability of the instrument was determined as follows: (1) Content validity by a panel of expert nurses; (2) predictive validity through a paired t-test analysis of preshift and postshift categorization of patients; (3) initial reliability by a one month pilot of the instrument in a practice setting; and (4) interrater reliability by the Kappa statistic.^ The nursing distribution system was a linear programming model using a branch and bound technique for obtaining integer solutions. The objective function was to minimize the total number of nursing personnel used by optimally assigning the staff to meet the acuity needs of the units. A penalty weight was used as a coefficient of the objective function variables to define priorities for allocation of staff.^ The demand constraints were requirements to meet the total acuity points needed for each unit and to have a minimum number of RNs on each unit. Supply constraints were: (1) total availability of each type of staff and the value of that staff member (value was determined relative to that type of staff's ability to perform the job function of an RN (i.e., value for eight hours RN = 8 points, LVN = 6 points); (2) number of personnel available for floating between units.^ The capability of the model to assign staff quantitatively and qualitatively equal to the manual method was established by a thirty day comparison. Sensitivity testing demonstrated appropriate adjustment of the optimal solution to changes in penalty coefficients in the objective function and to acuity totals in the demand constraints.^ Further investigation of the model documented: correct adjustment of assignments in response to staff value changes; and cost minimization by an addition of a dollar coefficient to the objective function. ^

3D Intervertebral Disc Localization and Segmentation from MR Images by Data-Driven Regression and Classification

In this paper we propose a new fully-automatic method for localizing and segmenting 3D intervertebral discs from MR images, where the two problems are solved in a unified data-driven regression and classification framework. We estimate the output (image displacements for localization, or fg/bg labels for segmentation) of image points by exploiting both training data and geometric constraints simultaneously. The problem is formulated in a unified objective function which is then solved globally and efficiently. We validate our method on MR images of 25 patients. Taking manually labeled data as the ground truth, our method achieves a mean localization error of 1.3 mm, a mean Dice metric of 87%, and a mean surface distance of 1.3 mm. Our method can be applied to other localization and segmentation tasks.

Monetary Policy Delegation, Contract Costs, and Contract Targets

We reconsider the optimal central banker contract derived in Walsh (1995). We show that if the government's objective function places weight (value) on the cost of the contract, then the optimal inflation contract does not completely neutralize the inflation bias. That is, a fraction of the inflation bias emerges in the resulting inflation rate after the central banker's monetary policy decision. Furthermore, the more concerned the government is about the cost of the contract or the less selfish (more benevolent) is the central banker, the smaller is the share of the inflation bias eliminated by the contract. No matter how concerned the government is about the cost of the contract or how unselfish (benevolent) the central banker is, the contract always reduces the inflationary bias by at least half. Finally, a central banker contract written in terms of output (i.e., incorporating an output target) can completely eradicate the inflationary bias, regardless of concerns about contract costs.

Input Aggregation in Models of Data Envelopment Analysis: A Statistical Test with an Application to Indian Manufacturing

A problem frequently encountered in Data Envelopment Analysis (DEA) is that the total number of inputs and outputs included tend to be too many relative to the sample size. One way to counter this problem is to combine several inputs (or outputs) into (meaningful) aggregate variables reducing thereby the dimension of the input (or output) vector. A direct effect of input aggregation is to reduce the number of constraints. This, in its turn, alters the optimal value of the objective function. In this paper, we show how a statistical test proposed by Banker (1993) may be applied to test the validity of a specific way of aggregating several inputs. An empirical application using data from Indian manufacturing for the year 2002-03 is included as an example of the proposed test.

EPANET Input Files of New York tunnels and Pacific City used in a metamodel-based optimization study

Metamodels have proven be very useful when it comes to reducing the computational requirements of Evolutionary Algorithm-based optimization by acting as quick-solving surrogates for slow-solving fitness functions. The relationship between metamodel scope and objective function varies between applications, that is, in some cases the metamodel acts as a surrogate for the whole fitness function, whereas in other cases it replaces only a component of the fitness function. This paper presents a formalized qualitative process to evaluate a fitness function to determine the most suitable metamodel scope so as to increase the likelihood of calibrating a high-fidelity metamodel and hence obtain good optimization results in a reasonable amount of time. The process is applied to the risk-based optimization of water distribution systems; a very computationally-intensive problem for real-world systems. The process is validated with a simple case study (modified New York Tunnels) and the power of metamodelling is demonstrated on a real-world case study (Pacific City) with a computational speed-up of several orders of magnitude.

Probabilistic models for the prediction of a ship performance in dynamic ice

We introduce two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is probable to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models to datasets were utilized. First, the data from the Automatic Identification System about the performance of a selected ship was used. Second, a numerical ice model HELMI, developed in the Finnish Meteorological Institute, provided information about the ice field. The relations between the ice conditions and ship movements were established using Bayesian learning algorithms. The case study presented in this paper considers a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. We expect this new approach to facilitate the safe and effective route selection problem for ice-covered waters where the ship performance is reflected in the objective function.

A new set of relativistic screening constants for the screened hydrogenic model

AnewRelativisticScreenedHydrogenicModel has been developed to calculate atomic data needed to compute the optical and thermodynamic properties of high energy density plasmas. The model is based on anewset of universal screeningconstants, including nlj-splitting that has been obtained by fitting to a large database of ionization potentials and excitation energies. This database was built with energies compiled from the National Institute of Standards and Technology (NIST) database of experimental atomic energy levels, and energies calculated with the Flexible Atomic Code (FAC). The screeningconstants have been computed up to the 5p3/2 subshell using a Genetic Algorithm technique with an objective function designed to minimize both the relative error and the maximum error. To select the best set of screeningconstants some additional physical criteria has been applied, which are based on the reproduction of the filling order of the shells and on obtaining the best ground state configuration. A statistical error analysis has been performed to test the model, which indicated that approximately 88% of the data lie within a ±10% error interval. We validate the model by comparing the results with ionization energies, transition energies, and wave functions computed using sophisticated self-consistent codes and experimental data.