Browsing by Keyword "Modeling and Simulation"
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Item A Comparison Between Coupled and Decoupled Vehicle Motion Controllers Based on Prediction Models(IEEE, 2019-06) Matute, Jose A.; Lattarulo, Ray; Zubizarreta, Asier; Perez, Joshue; CCAMIn this work, a comparative study is carried out with two different predictive controllers that consider the longitudinal jerk and steering rate change as additional parameters, as additional parameters, so that comfort constraints can be included. Furthermore, the approaches are designed so that the effect of longitudinal and lateral motion control coupling can be analyzed. This way, the first controller is a longitudinal and lateral coupled MPC approach based on a kinematic model of the vehicle, while the second is a decoupled strategy based on a triple integrator model based on MPC for the longitudinal control and a double proportional curvature control for the lateral motion control. The control architecture and motion planning are exhaustively explained. The comparative study is carried out using a test vehicle, whose dynamics and low-level controllers have been simulated using the realistic simulation environment Dynacar. The performed tests demonstrate the effectiveness of both approaches in speeds higher than 30 km/h, and demonstrate that the coupled strategy provides better performance than the decoupled one. The relevance of this work relies in the contribution of vehicle motion controllers considering the comfort and its advantage over decoupled alternatives for future implementation in real vehicles.Item Data driven model for heat load prediction in buildings connected to District Heating by using smart heat meters(2022-01-15) Lumbreras, Mikel; Garay-Martinez, Roberto; Arregi, Beñat; Martin-Escudero, Koldobika; Diarce, Gonzalo; Raud, Margus; Hagu, Indrek; Tecnalia Research & Innovation; EDIFICACIÓN DE ENERGÍA POSITIVAAn accurate characterization and prediction of heat loads in buildings connected to a District Heating (DH) network is crucial for the effective operation of these systems. The high variability of the heat production process of DH networks with low supply temperatures and derived from the incorporation of different heat sources increases the need for heat demand prediction models. This paper presents a novel data-driven model for the characterization and prediction of heating demand in buildings connected to a DH network. This model is built on the so-called Q-algorithm and fed with real data from 42 smart energy meters located in 42 buildings connected to the DH in Tartu (Estonia). These meters deliver heat consumption data with a 1-h frequency. Heat load profiles are analysed, and a model based on supervised clustering methods in combination with multiple variable regression is proposed. The model makes use of four climatic variables, including outdoor ambient temperature, global solar radiation and wind speed and direction, combined with time factors and data from smart meters. The model is designed for deployment over large sets of the building stock, and thus aims to forecast heat load regardless of the construction characteristics or final use of the building. The low computational cost required by this algorithm enables its integration into machines with no special requirements due to the equations governing the model. The data-driven model is evaluated both statistically and from an engineering or energetic point of view. R2 values from 0.70 to 0.99 are obtained for daily data resolution and R2 values up to 0.95 for hourly data resolution. Hourly results are very promising for more than 90% of the buildings under study.Item Direct route from ethanol to pure hydrogen through autothermal reforming in a membrane reactor: Experimental demonstration, reactor modelling and design: Experimental demonstration, reactor modelling and design(2018-01-15) Spallina, V.; Matturro, G.; Ruocco, C.; Meloni, E.; Palma, V.; Fernández-Gesalaga, E.; Melendez, J.; Pacheco Tanaka, David A.; Viviente Sole, J.L.; van Sint Annaland, M.; Gallucci, F.; Tecnalia Research & Innovation; TECNOLOGÍAS DE HIDRÓGENO; TECNOLOGÍA DE MEMBRANAS E INTENSIFICACIÓN DE PROCESOSThis work reports the integration of thin (∼3–4 μm thick) Pd-based membranes for H2 separation in a fluidized bed catalytic reactor for ethanol auto-thermal reforming. The performance of a fluidized bed membrane reactor has been investigated from an experimental and numerical point of view. The demonstration of the technology has been carried out over 50 h under reactive conditions using 5 thin Pd-based alumina-supported membranes and a 3 wt%Pt-10 wt%Ni catalyst deposited on a mixed CeO2/SiO2 support. The results have confirmed the feasibility of the concept, in particular the capacity to reach a hydrogen recovery factor up to 70%, while the operation at different fluidization regimes, oxygen-to-ethanol and steam-to-ethanol ratios, feed pressures and reactor temperatures have been studied. The most critical part of the system is the sealing of the membranes, where most of the gas leakage was detected. A fluidized bed membrane reactor model for ethanol reforming has been developed and validated with the obtained experimental results. The model has been subsequently used to design a small reactor unit for domestic use, showing that 0.45 m2 membrane area is needed to produce the amount of H2 required for a 5 kWe PEM fuel-cell based micro-CHP system.Item Fast Real-Time Trajectory Planning Method with 3rd-Order Curve Optimization for Automated Vehicles(IEEE, 2020-09-20) Lattarulo, Ray; Perez, Joshue; CCAMAutomated driving (AD) is one of the fastest-growing tendencies in the Intelligent Transportation Systems (ITS) field with some interesting demonstrations and prototypes. Currently, the main research topics are aligned with vehicle communications, environment recognition, control, and decision-making. A real-time trajectory planning method for Automated vehicles (AVs) is presented in this paper; the contribution is part of AD’s decision-making module. This novel approach uses the properties of the 3er order Bézier curves to generate fast and reliable vehicle trajectories. Online execution and vehicle tracking capacities are considered on the approach. A feasible trajectory is selected based on the criteria: (i) the vehicle must be contained by a collision-free corridor given by an upper decision layer, (ii) the vehicle must be capable to track the generated trajectory, and (iii) the continuity of the path and curvature must be preserved in the joints. Our approach was tested considering a vehicle length (automated bus) of 12 meters. The scenario has the dimension of a real test location with multiple roundabouts.Item Fault injection method for safety and controllability evaluation of automated driving(IEEE, 2017-07-31) Uriagereka, Garazi Juez; Lattarulo, Ray; Rastelli, Joshue Perez; Calonge, Estibaliz Amparan; Ruiz Lopez, Alejandra; Espinoza Ortiz, Huascar; Tecnalia Research & Innovation; CCAM; CIBERSEC&DLT; QuantumAdvanced Driver Assistance Systems (ADAS) and automated vehicle applications based on embedded sensors have become a reality today. As road vehicles increase its autonomy and the driver shares his role in the control loop, novel challenges on their dependability assessment arise. One key issue is that the notion of controllability becomes more complex when validating the robustness of the automated vehicle in the presence of faults. This paper presents a simulation-based fault injection approach aimed at finding acceptable controllability properties for the model-based design of control systems. We focus on determining the best fault models inserting exceptional conditions to accelerate the identification of specific areas for testing. In our work we performed fault injection method to find the most appropriate safety concepts, controllability properties and fault handling strategies at early design phases of lateral control functions based on the error in the Differential GPS signal.Item Influence of climate change externalities on the sustainability-oriented prioritisation of prospective energy scenarios(2020-04-01) Iribarren, Diego; Martín-Gamboa, Mario; Navas-Anguita, Zaira; García-Gusano, Diego; Dufour, Javier; Tecnalia Research & Innovation; PLANIFICACIÓN ENERGÉTICAThe implementation of externalities in energy policies is a potential measure for sustainability-oriented energy planning. Furthermore, decisions on energy policies and plans should be based on the analysis of a number of potential energy scenarios, considering the evolution of key techno-economic and life-cycle sustainability indicators. The joint interpretation of these multiple criteria should drive the choice of appropriate decisions for energy planning. Within this context, this work proposes –for the first time– the combined use of Life Cycle Assessment, externalities calculation, Energy Systems Modelling and dynamic Data Envelopment Analysis to prioritise prospective energy scenarios. For demonstration and illustrative purposes, the application of this methodological framework to the case study of electricity production in Spain leads to quantitatively discriminate between 15 prospective energy scenarios by taking into account the life-cycle profile of the transformation path of the power generation system with time horizon 2050. When compared to the application of the framework without implementation of external costs, the internalisation of climate change externalities is found to affect the ranking of energy scenarios but still showing the rejection of those scenarios based on the lifetime extension of coal power plants, as well as the preference for those scenarios leading to a high penetration of renewable technologies.Item Limitations and information needs for engineered nanomaterial-Specific exposure estimation and scenarios: Recommendations for improved reporting practices(2012-09) Clark, Katherine; Van Tongeren, Martie; Christensen, Frans M.; Brouwer, Derk; Nowack, Bernd; Gottschalk, Fadri; Micheletti, Christian; Schmid, Kaspar; Gerritsen, Rianda; Aitken, Rob; Vaquero, Celina; Gkanis, Vasileios; Housiadas, Christos; De Ipĩa, Jesús María López; Riediker, Michael; PRINTEX; SMART_MONThe aim of this paper is to describe the process and challenges in building exposure scenarios for engineered nanomaterials (ENM), using an exposure scenario format similar to that used for the European Chemicals regulation (REACH). Over 60 exposure scenarios were developed based on information from publicly available sources (literature, books, and reports), publicly available exposure estimation models, occupational sampling campaign data from partnering institutions, and industrial partners regarding their own facilities. The primary focus was on carbon-based nanomaterials, nano-silver (nano-Ag) and nano-titanium dioxide (nano-TiO2), and included occupational and consumer uses of these materials with consideration of the associated environmental release. The process of building exposure scenarios illustrated the availability and limitations of existing information and exposure assessment tools for characterizing exposure to ENM, particularly as it relates to risk assessment. This article describes the gaps in the information reviewed, recommends future areas of ENM exposure research, and proposes types of information that should, at a minimum, be included when reporting the results of such research, so that the information is useful in a wider context.Item A Linear Model Predictive Planning Approach for Overtaking Manoeuvres Under Possible Collision Circumstances(IEEE, 2018-10-18) Lattarulo, Ray; He, Daniel; Perez, Joshue; Heß, Daniel; CCAMOvertaking is one of the most difficult tasks during driving. This manoeuvre demands good skills to accomplish it correctly. In the overtaking considering multiple vehicles (more than a couple) is necessary to understand, predict and coordinate future actions of the other participants. These reasons make it a significant scenario for testing in the connected and automated driving field, with the main goal of predicting safe future states. In this sense, this work presents an overtaking method based on a linear Model Predictive Control (MPC) approach, which considers multiple participants involved in the scenario. This method adapts dynamically the trajectory for the manoeuvre in case of unexpected situations. Some of these changes consider other vehicles coming on the opposite lane or variations on participants' driving decisions. Additionally, the system considers passengers' comfort, the vehicle physical constraints and lateral actions of the vehicle decoupled of the longitudinal ones to simplify the problem.Item Mechanisms and Dynamics of Mineral Dissolution: A New Kinetic Monte Carlo Model: A New Kinetic Monte Carlo Model(2019-10-01) Martin, Pablo; Manzano, Hegoi; Dolado, Jorge S.; Tecnalia Research & InnovationMineral dissolution is a fundamental process in geochemistry and materials science. It is controlled by the complex interplay of atomic level mechanisms like adatoms and terraces removal, pit opening, and spontaneous vacancy creation that can be gradually activated at different energies.Item A plain linear rule for fatigue analysis under natural loading considering the coupled fatigue and corrosion effect(2019-05) Calderon-Uriszar-Aldaca, I.; Briz, E.; Biezma, M.V.; Puente, I.; Tecnalia Research & InnovationFatigue under variable amplitude loading is currently assessed by applying the Palmgren-Miner linear rule in structural standards. However, this linear rule is inadequate in natural scenarios with coupled fatigue and corrosion effects, because the coupled corrosion-fatigue process synergistically accelerates deterioration. In view of the absence of specifications for the coupled fatigue-corrosion effect in structural standards, the objective here is to develop a simple and practical correction factor that will ensure a conservative linear summation of damage, taking the corrosion-fatigue effect into account. The theoretical consistency and the feasibility of the new adapted rule are tested in a case study.Item A plain linear rule for fatigue analysis under natural loading considering the sequence effect(2017-10) Calderon-Uriszar-Aldaca, I.; Biezma, M.V.; Tecnalia Research & InnovationFatigue under variable amplitude loading is currently assessed with the Palmgren-Miner rule in structural standards, ignoring the order of loading, which would require non-linear or mixed rules, especially for the random loading sequences applied to certain structures. Therefore, the goal is to develop a practical and simple correction factor ensuring the linear summation of damage is conservative, so as to take the sequence effect into account in random loading from natural sources. The theoretical consistency of this approach is demonstrated and a case study is developed to test the feasibility of the new rule and its simplicity.Item Residential load forecasting under a demand response program based on economic incentives(2015-08-01) Ruiz, Nerea; Claessens, Bert; Jimeno, Joseba; Lopez, Jose Antonio; Six, Daan; POWER SYSTEMSThis paper describes a tool for an Aggregator to forecast the aggregated load demand response of a group of domestic customers subscribed to an indirect load control program based on price/volume signals. The tool employs a bottom-up approach based on physical end-use load models where the individual responses of a random sample of customers are combined in order to build the aggregated load demand response model. Simulation of the individual responses is carried out with an optimization algorithm based on mixed integer linear programming that minimizes the electricity bill whilst maintaining consumer's comfort level. To improve the performance of the model, a genetic algorithm for fitting the input parameters according to measured data is also provided. The tool is intended to allow the Aggregator rehearsing the impact of different control strategies and therefore choosing the most appropriate ones for market participation and portfolio optimization. To exemplify the methodological applicability of the developed algorithm, a case study based on an actual power system in eastern Spain is considered.Item Second-order fatigue of intrinsic mean stress under random loadings(2020-01) Calderón-Uríszar-Aldaca, Iñigo; Biezma, María Victoria; Matanza, Amaia; Briz, Estibaliz; Bastidas, David M.; Tecnalia Research & InnovationA fatigue process due to random loading that is progressively damaging a certain structural detail will vary in the presence of mean stresses. The variations are already considered in crack propagation laws and by applying equivalent 0-mean stress ranges from the Palmgren–Miner linear rule. Nevertheless, if the mean stress is intrinsic, instead of a direct consequence of the random loading, other second-order effects will have to be taken into account. Those effects are cycle quasi-ordering, histogram variations, and apparent mean tension, which are identified and defined in this study and, finally, developed in a case study for demonstrative purposes.Item Simulation of unglazed solar thermal systems integrated into façade & combined with ultra-low temperature district heating(International Building Performance Simulation Association, 2019) Lumbreras, Mikel; Garay, Roberto; Corrado, Vincenzo; Fabrizio, Enrico; Gasparella, Andrea; Patuzzi, Francesco; Tecnalia Research & InnovationThis paper presents a theoretical simulation of thermal and economical assessment of façade integrated Solar Thermal (ST) in combination with Ultra Low Temperature (ULT) District-Heating (DH). This paper is in line with existing R&D activities for the integration of unglazed systems in building envelopes, where facades provide an almost unexplored area for increasing solaractivated building envelopes. The combination of building-integrated solar systems with DH networks avoids the use of local storage and allows a novel combination of heat directionality, both from building to the heat grid and vice versa. A control algorithm for heat supply is presented, so that the performance of the overall system is the optimal. Energetic results from solar simulations and economic assessment derived from the balance of building energy demand and solar production are presented. Over a fullyear period the proposed unglazed system produces as much as 50% additional heat when compared with an isolated ST system and profitable economic metrics are reached over a simulation time of 20 years. Finally, it is concluded the heat sink nature of a DH network, for as many as 25-35% of the buildings connected to the DH includes ST system.Item Solving the multi-objective Hamiltonian cycle problem using a Branch-and-Fix based algorithm(2022-04) Murua, M.; Galar, D.; Santana, R.; FACTORY; Tecnalia Research & InnovationThe Hamiltonian cycle problem consists of finding a cycle in a given graph that passes through every single vertex exactly once, or determining that this cannot be achieved. In this investigation, a graph is considered with an associated set of matrices. The entries of each of the matrix correspond to a different weight of an arc. A multi-objective Hamiltonian cycle problem is addressed here by computing a Pareto set of solutions that minimize the sum of the weights of the arcs for each objective. Our heuristic approach extends the Branch-and-Fix algorithm, an exact method that embeds the problem in a stochastic process. To measure the efficiency of the proposed algorithm, we compare it with a multi-objective genetic algorithm in graphs of a different number of vertices and density. The results show that the density of the graphs is critical when solving the problem. The multi-objective genetic algorithm performs better (quality of the Pareto sets) than the proposed approach in random graphs with high density; however, in these graphs it is easier to find Hamiltonian cycles, and they are closer to the multi-objective traveling salesman problem. The results reveal that, in a challenging benchmark of Hamiltonian graphs with low density, the proposed approach significantly outperforms the multi-objective genetic algorithm.Item Surface integrity investigations for prediction of fatigue properties after machining of alloy 718(2021-03) Holmberg, Jonas; Wretland, Anders; Hammersberg, Peter; Berglund, Johan; Suárez, Alfredo; Beno, Tomas; FABRIC_INTELFatigue performance is crucial for gas turbine components, and it is greatly affected by the manufacturing processes. Ability to predict the expected fatigue life of a component based on surface integrity has been the objective in this work, enabling new processing methods. Alloy 718 samples were prepared by different machining setups, evaluated in fatigue testing and surface integrity investigations. These results generated two predictive statistical multi-variate regression models. The fatigue correlated well with roughness, residual stresses and deformation. The two models showed great potential, which encourages further exploration to fine-tune the procedure for the particular case.Item Thermodynamic, economic and environmental assessment of energy systems including the use of gas from manure fermentation in the context of the Spanish potential(2020-06-01) Skorek-Osikowska, Anna; Martin-Gamboa, Mario; Iribarren, Diego; García-Gusano, Diego; Dufour, Javier; Tecnalia Research & Innovation; PLANIFICACIÓN ENERGÉTICAOne of the prospective technologies that can be used for energy generation in distributed systems is based on biogas production, usually involving fermentation of various types of biomass and waste. This article aims to bring novelty on the analysis of this type of systems, joining together thermodynamic, economic and environmental aspects for a cross-cutting evaluation of the proposed solutions. The analysis is made for Spain, for which such a solution is very promising due to availability of the feedstock. A detailed simulation model of the proposed system in two different cases was built in Aspen Plus software and Visual Basic for Applications. Case 1 involves production of biogas in manure fermentation process, its upgrading (cleaning and removal of CO2 from the gas) and injection to the grid. Case 2 assumes combustion of the biogas in gas engine to produce electricity and heat that can be used locally and/or sold to the grid. Thermodynamic assessment of these two cases was made to determine the most important parameters and evaluation indices. The results served as input values for the economic analysis and environmental evaluation through Life Cycle Assessment of the energy systems. The results show that the analysed technologies have potential to produce high-value products based on low-quality biomass. Economic evaluation determined the break-even price of biomethane (Case 1) and electricity (Case 2), which for the nominal assumptions reach the values of 16.77 €/GJ and 28.92 €/GJ, respectively. In terms of environmental assessment the system with the use of biogas in gas engine presents around three times better environmental profile than Case 1 in the two categories evaluated, i.e., carbon and energy footprint.Item Transfer Learning and Online Learning for Traffic Forecasting under Different Data Availability Conditions: Alternatives and Pitfalls(Institute of Electrical and Electronics Engineers Inc., 2020-09-20) Manibardo, Eric L.; Laña, Ibai; Del Ser, Javier; IAThis work aims at unveiling the potential of Transfer Learning (TL) for developing a traffic flow forecasting model in scenarios of absent data. Knowledge transfer from high-quality predictive models becomes feasible under the TL paradigm, enabling the generation of new proper models with few data. In order to explore this capability, we identify three different levels of data absent scenarios, where TL techniques are applied among Deep Learning (DL) methods for traffic forecasting. Then, traditional batch learning is compared against TL based models using real traffic flow data, collected by deployed loops managed by the City Council of Madrid (Spain). In addition, we apply Online Learning (OL) techniques, where model receives an update after each prediction, in order to adapt to traffic flow trend changes and incrementally learn from new incoming traffic data. The obtained experimental results shed light on the advantages of transfer and online learning for traffic flow forecasting, and draw practical insights on their interplay with the amount of available training data at the location of interest.