a vector optimization methodology applied to thermodynamic model calibration of a micro gas turbine chp plant

Abstract This paper is focused on the validation of a cogeneration plant based on micro gas turbine. The experimental data related to design working point are compared to thermodynamic model results using a multi-variable multi-objective methodology depending on a genetic optimization algorithm (MOGA-II). The result with lowest Euclidean norm in objective functions space represents the operating conditions closest to experimental data, and it highlights at the same time the reliability of chain measurement. Finally, this preferred result is plotted on turbomachinery performance maps in order to validate indirectly the methodology outcomes

effects of uncertainties on the stability of the results of an optimal sized modular cogeneration plant

Abstract In the last decades, the growing concerns about global warming and climate changes effects led to specific Directive, especially in Europe, promoting the use of primary energy saving techniques. In particular, a more widespread adoption of cogeneration systems has been obtained. However, distributed energy systems do not ensure the achievement of primary energy and cost savings without a proper sizing and operation of the plant. Therefore, vector optimization algorithms could play a key role to identify optimal solutions even when conflicting goals are pursued. The potential of the proposed methodology is demonstrated showing the results achieved from a specific application

thermodynamic model validation of capstone c30 micro gas turbine

Abstract In this work, a multi-variable multi-objective methodology aimed to perform the validation of the thermodynamic model has been applied to the Capstone C30 micro gas turbine. The methodology is based on a genetic optimization algorithm, where decision variables and objectives are set depending on available experimental data. The results of the studied case highlight the capability of the method to point out some experimental data inconsistencies and that it can lead to a consistency thermodynamic reconstruction of the micro turbine behaviour

Review on Battery State Estimation and Management Solutions for Next-Generation Connected Vehicles

The transport sector is tackling the challenge of reducing vehicle pollutant emissions and carbon footprints by means of a shift to electrified powertrains, i.e., battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). However, electrified vehicles pose new issues associated with the design and energy management for the efficient use of onboard energy storage systems (ESSs). Thus, strong attention should be devoted to ensuring the safety and efficient operation of the ESSs. In this framework, a dedicated battery management system (BMS) is required to contemporaneously optimize the battery’s state of charge (SoC) and to increase the battery’s lifespan through tight control of its state of health (SoH). Despite the advancements in the modern onboard BMS, more detailed data-driven algorithms for SoC, SoH, and fault diagnosis cannot be implemented due to limited computing capabilities. To overcome such limitations, the conceptualization and/or implementation of BMS in-cloud applications are under investigation. The present study hence aims to produce a new and comprehensive review of the advancements in battery management solutions in terms of functionality, usability, and drawbacks, with specific attention to cloud-based BMS solutions as well as SoC and SoH prediction and estimation. Current gaps and challenges are addressed considering V2X connectivity to fully exploit the latest cloud-based solutions

Pre-lift Valve Actuation Strategy for the Performance Improvement of a DISI VVA Turbocharged Engine

Abstract Modern internal combustion engines (ICEs) are becoming more and more complex in order to achieve not only better power and torque performance, but also to respect the pollutant emissions and the fuel consumption (CO 2 ) limits. The turbocharger, advanced valve actuation systems (VVA) and the EGR circuit allow the ICE's load control together with the traditional throttle valve and spark advance. Thus, an higher number of operating parameters are available for the calibration engineer to achieve the required performance target (minimum fuel consumption at part load, maximum power and torque at full load, etc.). On the other hand, the increased degrees of freedom may frustrate the potentialities of so complex systems because of the effort needed to identify the optimal engine control strategies. The development of proper numerical models may assist and direct the experimental activity in order to reduce the related times and costs. Although VVA solutions could bring a reduction in the specific fuel consumption thanks to an important de-throttling of the intake system, unfortunately they can simultaneously lead to higher noise levels radiated by the intake mouth. In fact, in this case, the pressure waves travelling through the intake ducts are not properly damped by the throttle valve. In this paper a numerical methodology is developed to define the engine calibration and the intake valve lift profile that simultaneously minimize the BSFC and the noise at part load. The engine object of the study is a turbocharged Spark-Ignition Direct Injection (SIDI) ICE equipped by a lost motion valve actuation system for the intake valves. In this study, the commercial 1D thermo fluid-dynamic code GT-PowerTM is provided with user routines for the description of the combustion process and the handing of variable valve lift profiles. The engine model is thus integrated with a commercial optimization code (modeFRONTIERTM) to identify the optimized load control strategies to achieve the set objectives. The proposed methodology is also used for the definition of unconventional valve lift profiles. Particularly, the advantages related to the use of a small pre-lift before the main valve lift profile are estimated compared to a conventional EIVC strategy

A Review of Model Predictive Controls Applied to Advanced Driver-Assistance Systems

Advanced Driver-Assistance Systems (ADASs) are currently gaining particular attention in the automotive field, as enablers for vehicle energy consumption, safety, and comfort enhancement. Compelling evidence is in fact provided by the variety of related studies that are to be found in the literature. Moreover, considering the actual technology readiness, larger opportunities might stem from the combination of ADASs and vehicle connectivity. Nevertheless, the definition of a suitable control system is not often trivial, especially when dealing with multiple-objective problems and dynamics complexity. In this scenario, even though diverse strategies are possible (e.g., Equivalent Consumption Minimization Strategy, Rule-based strategy, etc.), the Model Predictive Control (MPC) turned out to be among the most effective ones in fulfilling the aforementioned tasks. Hence, the proposed study is meant to produce a comprehensive review of MPCs applied to scenarios where ADASs are exploited and aims at providing the guidelines to select the appropriate strategy. More precisely, particular attention is paid to the prediction phase, the objective function formulation and the constraints. Subsequently, the interest is shifted to the combination of ADASs and vehicle connectivity to assess for how such information is handled by the MPC. The main results from the literature are presented and discussed, along with the integration of MPC in the optimal management of higher level connection and automation. Current gaps and challenges are addressed to, so as to possibly provide hints on future developments

Molecular Mechanisms Generating and Stabilizing Terminal 22q13 Deletions in 44 Subjects with Phelan/McDermid Syndrome

In this study, we used deletions at 22q13, which represent a substantial source of human pathology (Phelan/McDermid syndrome), as a model for investigating the molecular mechanisms of terminal deletions that are currently poorly understood. We characterized at the molecular level the genomic rearrangement in 44 unrelated patients with 22q13 monosomy resulting from simple terminal deletions (72%), ring chromosomes (14%), and unbalanced translocations (7%). We also discovered interstitial deletions between 17–74 kb in 9% of the patients. Haploinsufficiency of the SHANK3 gene, confirmed in all rearrangements, is very likely the cause of the major neurological features associated with PMS. SHANK3 mutations can also result in language and/or social interaction disabilities. We determined the breakpoint junctions in 29 cases, providing a realistic snapshot of the variety of mechanisms driving non-recurrent deletion and repair at chromosome ends. De novo telomere synthesis and telomere capture are used to repair terminal deletions; non-homologous end-joining or microhomology-mediated break-induced replication is probably involved in ring 22 formation and translocations; non-homologous end-joining and fork stalling and template switching prevail in cases with interstitial 22q13.3. For the first time, we also demonstrated that distinct stabilizing events of the same terminal deletion can occur in different early embryonic cells, proving that terminal deletions can be repaired by multistep healing events and supporting the recent hypothesis that rare pathogenic germline rearrangements may have mitotic origin. Finally, the progressive clinical deterioration observed throughout the longitudinal medical history of three subjects over forty years supports the hypothesis of a role for SHANK3 haploinsufficiency in neurological deterioration, in addition to its involvement in the neurobehavioral phenotype of PMS

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection