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Evaluation of the dynamic load test on bored piles in sandy soil

Evaluation of the dynamic load test on bored piles in sandy soil

Several attempts have been made to evaluate the prediction of pile capacity using dynamic load testing. Likins and Rausche (2004) have compiled a summary of different studies related to the stress wave conferences and found a good agreement comparing the results of static and dynamic load tests in their database. The results depend on the type of piles and are generally more convincing for driven piles than for bored piles. Whenever differences are found between DLT and SLT, lower values for the pile capacities are obtained in the dynamic load tests, which at least would be on the safe side. However, due to the lack of full background information it is not clear whether static and dynamic load test results were evaluated completely independent in all cases.
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Comparison of static and dynamic load tests on bored piles in glacial soil

Comparison of static and dynamic load tests on bored piles in glacial soil

dynamic load capacity evaluation of bored piles in glacial sandy soil. The test was performed using eight piles at the BAM test site for technical safety at Horstwalde 50 km south of Berlin. The test area has been prepared and investigated in great detail using boreholes, cone penetration tests, pore pressure sensors and geophysical methods to assure controlled conditions for all piles and tests. The piles (10 m length, 0.9 m diameter) are mainly friction piles (low toe resistance) and have been checked by integrity testing. Five piles have been tested by five contractors using the dynamic method in a blind experiment, the other ones piles by static load and/or later on by the dynamic method. Some piles have been equipped with additional fibre optic instrumentation which proved to be robust and helpful in interpreting the results of static, dynamic and integrity tests. We have experienced a deviation of the dynamic load test results gathered in the blind experiment from the static values of up to 20% in most cases, sometimes even up to 30%. This can be related to the known soil inhomogeneities, interpretation and modelling in CAPWAP and method inherent uncertainties. In cases where the static values were known by the testers for calibration, the deviations were significantly smaller. It has to be taken into account, that the two static load tests showed different results as well. Due to the low toe resistance, use of a big drop weight (11 tons) and large drop heights most piles suffered from cracking, which was clearly seen in follow up integrity tests and confirmed by excavation. The piles are available for further research.
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Application and machine learning methods for dynamic load point controls of electric vehicles (xEVs)

Application and machine learning methods for dynamic load point controls of electric vehicles (xEVs)

Unlike before, the goal of this work is to use ML techniques to predict the charging load and modularly integrate it into an intelligent charging management system. As a further step, the dynamic load management methods can be applied to flatten the load curve with the help of predefined schedules. This is generally done by reducing the simultaneous factor and thus leads to a reduced load at the grid connection point. In addition, it is relevant to refer to the data that is actually available. Obtaining information from the vehicles like the state of charge (SOC) or energy demand seems realistic, but there would have to be digital communication with the charging station, which would require both the vehicle and the charging station to be ISO-15118 compliant (in Europe) [6]. As current instruments on the market do not yet fully support this technology, this criterion is not applicable. Therefore, in addition to the measurement data of the charging stations, which are provided by the charging station operators, it is advantageous to obtain further information on the environment. Thus, the features described in this paper come very close to those as they were set up in [7], whereby weather and time- related information such as holidays, weekdays etc. prove to be expedient.
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Parallel adaptive FETI-DP using lightweight asynchronous
dynamic load balancing

Parallel adaptive FETI-DP using lightweight asynchronous dynamic load balancing

A parallel FETI-DP domain decomposition method using an adaptive coarse space is presented. The implementation builds on a recently introduced adaptive FETI-DP approach for elliptic problems in three dimensions and uses small, local eigenvalue problems for faces and, additionally, for a small number of edges. The condition number of the preconditioned operator then satisfies a bound which is independent of coefficient heterogeneities in the problem. The computational cost of the local eigenvalue problems is not negligible, and also a significant load imbalance can be introduced. As a remedy, certain eigenvalue problems are discarded by a theory- guided heuristic strategy, based on the diagonal entries of the stiffness matrices. Additionally, a lightweight pairwise dynamic load balancing strategy is implemented for the eigenvalue problems. The load balancing is supervised by an orchestrating rank using asynchronous point-to-point communication. The resulting method shows good weak and strong scalability up to thousands of cores while fast convergence is obtained even for heterogeneous problems.
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Uncertainty evaluation of semi-active load redistribution in a mechanical load-bearing structure

Uncertainty evaluation of semi-active load redistribution in a mechanical load-bearing structure

The investigated load-bearing structure in this thesis is based on the load- bearing structure developed within the SFB 805 and consists of a translational moving mass connected to a rigid beam by a spring-damper system and two semi- active guidance elements with the ability to redistribute loads according to the proposed concept. The beam is supported at its ends by two supports. The stiffness characteristic of the supports can be adjusted to simulate structural damage with reduced support stiffness. The semi-active guidance elements can provide addi- tional load paths to relieve the damaged parts of the structure. This load-bearing structure was used to numerically and experimentally evaluate the load redistribu- tion capability with semi-active friction brakes in the guidance elements to provide additional load paths. An experimental test setup of the load-bearing structure was designed to investigate the load redistribution capability based on measured data. A step-like dynamic load was applied to the load-bearing structure as excita- tion. In order to redistribute the load between the two supports via the semi-active guidance elements, two different control strategies were tested. Combined with a clipped-optimal linear-quadratic regulator (LQR), control strategy I aims to re- duce undesired beam misalignment that is defined as malfunction and is caused by a damaged support. Combined with a clipped-optimal PID controller, control strategy II aims to precautionary achieve a desired load ratio between the supports before a damage occurs. Additionally, the load path was analyzed and evaluated by means of the resulting support reaction forces.
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Operation of SOFC 4-Cell Stack under Dynamic Electronic Load

Operation of SOFC 4-Cell Stack under Dynamic Electronic Load

Development of SOFCs in Europe focuses on fuel cell systems for generating power and heat in residential and commercial buildings, so called micro CHPs. One of the areas of interest is the dynamic operation of SOFCs and how it affects the durability of the stacks. Dynamic load operation of SOFCs is an important topic since energy demand in small scale house applications varies a lot during the day [1] and therefore quick response times to changes in electrical power demand are crucial for such a system, especially if no electric grid back-up is available for instance due to remote location or if the system is linked with other renewable energy systems like photovoltaics or wind power which also tend to vary a lot and where precise forecasts of wind and solar exposure still have a large margin of error [2, 3, 4].
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Techno-economic evaluation of load activation quotas as a concept for flexible load management

Techno-economic evaluation of load activation quotas as a concept for flexible load management

1 Institute for High Voltage Technology (IFHT), RWTH Aachen University, Aachen, Germany 2 Technik Innovation (TI), Netze BW GmbH, Stuttgart, Germany ✉ E-mail: thie@ifht.rwth-aachen.de Abstract: Flexible load management concepts are increasingly relevant due to a rising share of flexibilities at distribution grid level, e.g. power-to-heat systems, electric vehicles or home battery storages. In a market oriented load management, uniform price signals can lead to higher load simultaneity factors and grid congestions. Therefore, load management concepts have to consider the prevention of grid congestions, e.g. by load activation quotas. The quota represents the maximum share of flexible loads per grid segment for each point in time that can be activated without causing grid congestions. Grid expansion measures increase the possible activation quota and lead to higher flexibility in operation. For an aggregator of flexible loads, grid expansion increases the potential for procurement cost reduction. On the other side, it causes capital costs for the distribution system operator. This study introduces a methodology for the techno-economic evaluation of LAQ as a concept for flexible load management in future distribution grids, which is applied to an exemplary medium-voltage grid in Southern Germany. The analysis considers both the investment costs for grid expansion by the grid operator and operational savings in procurement due to an increased flexibility for an aggregator. The cost-efficient trade-off from a micro-economic perspective is determined.
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Dynamic IC and dynamic programming

Dynamic IC and dynamic programming

doesn’t generalize immediately without taking into account private histories and multi-period deviations. As for examples of when one-stage deviation principle in the usual sense doesn’t hold and one might need to worry about the dynamic IC, consider any stochastic game with private information of players. Any repeated game with private monitoring and a discount factor strictly bounded away from one also requires taking care of this issue. If the agent can have private information and also take an action privately, then dynamic mechanism design also needs to deal with multi-period deviations in general. The two sufficient conditions I provide in Kwon (2019) are (i) learning models with symmetric uncertainty and (ii) agents observing the payoff-relevant state perfectly every period in the Markovian environment. Otherwise, in any model with a fully-persistent state that is the agent’s private information, one cannot rule out multi-period deviations a priori.
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Techno-economic evaluation of load activation quotas as a concept for flexible load management

Techno-economic evaluation of load activation quotas as a concept for flexible load management

1 Institute for High Voltage Technology (IFHT), RWTH Aachen University, Aachen, Germany 2 Technik Innovation (TI), Netze BW GmbH, Stuttgart, Germany ܂ E-mail: thie@ifht.rwth-aachen.de Abstract: Flexible load management concepts are increasingly relevant due to a rising share of flexibilities at distribution grid level, e.g. power-to-heat systems, electric vehicles or home battery storages. In a market oriented load management, uniform price signals can lead to higher load simultaneity factors and grid congestions. Therefore, load management concepts have to consider the prevention of grid congestions, e.g. by load activation quotas. The quota represents the maximum share of flexible loads per grid segment for each point in time that can be activated without causing grid congestions. Grid expansion measures increase the possible activation quota and lead to higher flexibility in operation. For an aggregator of flexible loads, grid expansion increases the potential for procurement cost reduction. On the other side, it causes capital costs for the distribution system operator. This study introduces a methodology for the techno-economic evaluation of LAQ as a concept for flexible load management in future distribution grids, which is applied to an exemplary medium-voltage grid in Southern Germany. The analysis considers both the investment costs for grid expansion by the grid operator and operational savings in procurement due to an increased flexibility for an aggregator. The cost-efficient trade-off from a micro-economic perspective is determined.
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Regulierung des Netzmonopolisten durch Verbot von Peak-load Pricing?

Regulierung des Netzmonopolisten durch Verbot von Peak-load Pricing?

Während in der Literatur bis Anfang der 90er Jahre wenige Phänomene von vielen Auto- ren untersucht worden sind und so das Basismodell schrittweise erweitert wurde, werden in der neueren Literatur sehr verschiedene Aspekte, diese jedoch nur von einzelnen Autoren be- trachtet. So modellieren Lecinq/Ilic (1997) das Netz inklusive seiner räumlichen Ausdehnung, um Peak-load Pricing für das Netz zu untersuchen, vernachlässigen jedoch Kapazitätskosten der Stromerzeugung und Transportkosten des Stroms im Netz. Sie betonen zwar die Wichtig- keit sinkender Durchschnittskosten für ihr Modell, bilden es dennoch mit konstanten Durch- schnittskosten. Pillai (2003) plädiert für eine Aufteilung der Kapazitätskosten auf die ver- schiedenen Nachfragen entsprechend ihrer relativen Inanspruchnahme der vorhandenen Ka- pazität. Er folgt ebenfalls dem traditionellen Ansatz mit konstanten Durchschnittskosten und einstufiger Modellierung des Stromsektors. Ksoll (2003) untersucht Effekte vertikaler Tren- nung bei verschiedenen Preissystemen und Marktformen, thematisiert allerdings Spitzenlast- preisbildung nicht. Ein Schwerpunkt in der neueren Literatur ist die Betrachtung interdepen- denter Nachfragen, d.h. die Verlagerung der Nachfragen durch zeitlich differenzierte Preisgestaltung. Horsley/Wrobel (2001) betrachten kontinuierliche Preise und interdependente Nachfragen, bilden aber den Strommarkt weder zweistufig noch mit sinkenden Durch- schnittskosten ab. Genauso verfährt Rocco (2003), der ein Spiel modelliert, in dem die nut- zenmaximierenden Individuen den Zeitpunkt ihrer Nachfrage in Abhängigkeit von den Prei- sen treffen, die wiederum von den Nachfrageentscheidungen aller anderen Mitspieler abhän- gen. So versucht er, die Höhe der Nachfrage zu jedem Zeitpunkt endogen zu erklären. Ein weiterer Schwerpunkt der neueren Literatur ist das Abrücken von der Annahme des wohl- fahrtsmaximierenden integrierten Stromunternehmens und die Untersuchung der dann entste- henden Probleme des Wohlfahrtsverlustes durch gewinnmaximierende Preissetzung des Monopolisten.
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Signal based non-intrusive load decomposition

Signal based non-intrusive load decomposition

Trough the rapid expansion of load sensors and smart meters the analysis of various loads continuously gains more attention. For example, there is a great interest in decomposing an electrical grid’s load since grid operators need to estimate the demand but usually has no information about his consumer’s behaviors. Paisios proposes a method to decompose and profile the load for demand side management [2]. This has recently lead to the development of algorithms for non-intrusive load monitoring (NILM) techniques, which aim to assign a meter’s load to the compo- nents connected to the meter. NILM often focuses on household meters to detect loads of various common household equipment [3]. The initial approach for NILM was proposed by Hart in 1992 and gained attention through the in- creasing digitalization over the last years ([3], [4], [5]). These algorithms aim to detect component states by analyzing the load profile. Often not just the load but also additional characteristics like harmonics are used like Srinivasan’s analysis of loads with neural networks [6]. Like stated by Saitoh NILM can identify several component’s states by analyzing the load [7]. Usually NILM requires the installation of smart meters that provide detailed measurements of the load, so these concepts aim for the design phase of electrical systems [8]. However, previous mentioned re- search focuses on analyzing load to allocate the load to the components or identify states via unsupervised learning methods. On industrial levels there is often no need to identify states of components since they are already recorded for other purposes like production planning and controlling. Energy monitoring systems also usually record just the power demand and no additional load information. An approach to decompose energy data in an industrial scale using NILM was proposed in by Holmegaard along with an analysis of the challenges, however not combining energy data with other production information [9]. Abele presents an analysis of a milling machine whose load is allocated to its components using PLC signals [10]. Ebersp¨acher presents a similar approach but uses PLC signals as an input for a Model to determine the load via simulations [11] and Gebbe presents a decomposition approach using machine states and processing this data through a linear regression model [12]. The database of Gebbe’s evaluation is quite similar to case study 2 in this paper, with different levels of state details though.
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Cognitive load increases risk aversion

Cognitive load increases risk aversion

Our results confirm and extend the results reported by Benjamin et al. ( 2013 ) who found a significant increase of risk aversion under cognitive load only for a subset of the choices that their subjects had made: for risky–risky trials, but not for safe–risky trials— with the point estimate for the safe–risky trials nevertheless being of the same sign. An ex- planation for the lack of a significant finding for the safe–risky trials in their study may be the combination of a rather low number of trials with a ceiling effect: just like in our study, their subjects showed pronounced risk aversion in safe–risky trials even in the absence of load, so that there is not much room for cognitive load to increase risk aversion even further. In contrast to Benjamin et al., we actually find stronger evidence that cognitive load increases risk aversion in the safe–risky trials than in the risky–risky trials when we use the count measure of how often subjects chose the less risky option ( Section 4.1 ). This is also in line with the theoretical predictions of Fudenberg and Levine ( 2011 ).20 However, in the complementary analysis via structural regressions, we observe a significant load- induced increase in risk aversion only when pooling the risky–risky and the safe–risky tri- als or when analyzing the risky–risky trials alone ( 4.3.2 ). Even though the point estimates for the load-induced increases in risk aversion are virtually identical in the safe–risky and the risky–risky trials, the effect does not reach significance in the safe–risky trials—similar to the results of Benjamin et al.
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Disaggregation of household load profiles

Disaggregation of household load profiles

 Identification of complete load profiles: The first three steps may lead to partially incomplete load profiles. It’s possible that some appliances contain a heating phase which occurs later than the distance defined for extracting the intervals. Therefore, the determined load profiles are used to identify similar sections during the full year’s load data. As soon as an interval with the same length exceeds the selected correlation coefficient, an interval with a fixed length (here: 150 min) is extracted. It may be expected that the maximum program duration of the three considered appliances amounts to approximately 150 min.
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Implikationen der Cognitive Load Theory für das Controlling

Implikationen der Cognitive Load Theory für das Controlling

Grundlagen der Cognitive Load Theory chung eingesetzt. Zum Messen der mentalen Anstrengung und der Leistungsergebnisse kom- men empirische Methoden zum Einsatz. Dabei lassen sich zwei verschiedene Techniken un- terscheiden: einerseits subjektive Techniken, die auf der Bewertung durch Probanden mittels Ratingskalen basieren, und andererseits objektive Techniken wie z. B. psychophysiologische Tests, bei denen die Gehirnaktivitäten, die Herzschlagfrequenz oder die Veränderung des Pu- pillendurchmessers aufgezeichnet werden. 69 Ratingskalenverfahren basieren auf der Annah- me, dass die Testpersonen in der Lage sind, zuverlässige Aussagen über ihre kognitiven Pro- zesse und die mentale Anstrengung zu treffen und stellen die meistgenutzte Variante bei den bisher durchgeführten Experimenten zur Messung der kognitiven Belastung dar. 70 Psycho- physiologischen Techniken liegt die Annahme zugrunde, dass Veränderungen in der kogniti- ven Belastung sich in den Reaktionen physiologischer Funktionsbereiche des Menschen wi- derspiegeln. 71 Sie eignen sich besonders gut, um zeitliche Verläufe der kognitiven Belastung aufzunehmen. Bei den Problem- und Leistungsergebnismessungen lassen sich zwei Vorgehen unterscheiden. Die erste Variante besteht darin, die erbrachten Ergebnisse bei der Primary Task, also beim Hauptproblem, zu messen. Bei der zweiten Variante, auch als Dual-Task- Methode bezeichnet, bearbeitet der Problembearbeiter parallel zum Hauptproblem noch ein Nebenproblem, bei dem im Regelfall einfache Handlungen vollzogen werden, die jedoch kon- tinuierlicher Aufmerksamkeit bedürfen. Haupt- und Nebenproblem konkurrieren daher um die vorhandenen kognitiven Kapazitäten. Die Nebenprobleme werden häufig anhand von Re- aktionszeiten, erreichten Genauigkeiten und Fehlerraten bewertet. 72
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Dynamic similarity

Dynamic similarity

Allowing for volume forces, either due to gravity or to inertial forces, their relative importance is controlled by similar dimensionless parameters (Sec.. velocity for a given flow.[r]

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Quantification of nonlinear effects in gust load prediction

Quantification of nonlinear effects in gust load prediction

Fig. 5 shows the time signals of the GAFs for the gust amplitudes of 10m/s and 15m/s with five different gust lengths. The signals show qualitatively comparable results for both amplitudes. The case of 15m/s results in significantly higher forces and steeper gradients. For both cases, it can be observed that the highest GAFs occur for the mid-sized gust lengths. Furthermore, the gust length with the maximal forces may change with increasing gust ampltiude as it can be seen for the minimum bending force for a gust length of 66m. In combination with the steeper gradients, this displays the presence of some nonlinearity with increasing gust amplitude. From the loads recovery analysis, cf. Eq. (3), the loads envelope can be extracted by taking the maximum and minimal loads at each station over time. Thus, the loads envelopes describe the limits of the loads while the aircraft is encountering the gust. Fig. 6 shows the load envelopes of the wing bending moment ∆M x for the gust amplitudes of 10m/s and 20m/s and multiple
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Cardiorespiratory assessment of mental load in Pilot selection

Cardiorespiratory assessment of mental load in Pilot selection

order to reduce possible effects of anticipatory arousal with a minimally demanding vigilance task (Jennings et al., 1992). Since the presented vigilance task, however, was not accompanied by lower respiratory levels than the resting baseline, only resting baseline data were used for the statistical analysis of baseline-to-task changes. To induce mental load in a way that is similar to the cockpit workload of a civilian aircraft, a highly demanding multiple task was chosen which consisted of three single tasks measuring perceptual speed, spatial orientation, and working memory capacity, which had to be carried out in parallel. The perceptual speed task required the simultaneous scanning of four instruments. The pointer of each instrument indicated one of eight directions (Figure 1a). The task was to detect the number of instruments showing the same value. The spatial orientation task measured mental rotation and spatial processing ability. A pictogram of an aircraft was shown that could be rotated around its center, pointing in one of 12 directions (comparable to a clock face). In addition, a spot was shown in one of the 12 positions on an imaginary circle around the aircraft (Figure 1b). Participants had to indicate the spot’s position (clockwise 1–12) relative to the center and flight direction of the aircraft. The working memory task required memorizing pairs of colors (grey, blue, brown, green) and two-digit numbers that were presented acoustically (e.g., “green two eight”). A two-digit number was displayed on the screen (Figure 1c), continuously increasing from 13 to 99. The number changed every four seconds. As soon as one of the acoustically given numbers appeared on the screen, subjects had to click on the
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Cognitive load measurement while learning with multimedia

Cognitive load measurement while learning with multimedia

Based on the criticism about missing unique characteristics needed to distinguish between intrinsic and germane cognitive load, an updated model of CLT considers only two of the three components: intrinsic and extraneous cognitive load (Choi et al., 2014; Kalyuga, 2011). The deletion of germane load was due to the close relationship between intrinsic and germane cognitive load, which manifested in the inability to separate a unique contribution of each factor to the overall cognitive load. Germane cognitive load is now considered as germane resources that reflect the actually allocated amount of working memory capacity for learning and the learners’ engagement in the learning activity (Sweller, 2010). Germane cognitive resources can be increased by instructional techniques that increase the learners’ engagement in the learning activity. The cognitive load that is caused by schema acquisition is incorporated into the intrinsic cognitive load factor as intrinsic cognitive load represents the essential processing of the learning task. Instructional techniques to foster schema acquisition and to increase former germane cognitive load are assumed to raise the number of interacting elements and to belong to intrinsic cognitive load within the updated model. Element interactivity remains the crucial factor for intrinsic cognitive load and the cognitive demands of the learning task. However, the task characteristics are further redefined according to the intrinsic task difficulty, the type of task and the manner of instructional design and distinguished from the physical learning environment. The physical learning environment is considered as a surrounding situational factor that interacts with the learner and the task characteristics and has cognitive, physiological and affective effects on learning (Choi et al., 2014). The effects of the physical learning environment can cause additional extraneous cognitive load, for example via seductive noise that has to be ignored and affects the focus of attention, but they can also foster germane cognitive resources, for example by providing a motivating learning environment. In sum, the updated model not only reduced the number of capacity consuming load factors but also adapted to cognitive-affective, motivational and evolutionary perspectives and theories.
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Wind load reduction for light-weight heliostats

Wind load reduction for light-weight heliostats

The resulting pressure difference between top and bottom of the facet leads to high pressure coefficients (cp-values) near the frontal edge which leads to the peak overturning moment.[r]

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Wind load reduction for light-weight heliostats

Wind load reduction for light-weight heliostats

At SolarPACES 2012 conference a new heliostat concept was presented. It is equipped with wireless communication, sandwich facets, wind protection devices for wind load reduction, rim drives with winch wheels and ground anchor foundation. Crucial for the development of the light-weight structures is the precise determination of the maximum loads. By full scale wind load measurements the duration of the peak loads could be determined. They are caused by gusts with such short duration that their energy can be dissipated by shock absorbers protecting the structure. Furthermore, the wind loads can be reduced by wind protection devices. For the design-relevant stow position, a reduction in structural loading of 40 % can be achieved by the wind protection devices as wind tunnel tests have shown. The reduced loading has a significant impact on the dimensioning and cost of the structure and foundation of the heliostat. The systems for wind load reduction can be used for any kind of heliostat to reduce weight and cost.
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