scispace - formally typeset
Search or ask a question
Author

Claudio Martani

Bio: Claudio Martani is an academic researcher from ETH Zurich. The author has contributed to research in topics: Risk management & User requirements document. The author has an hindex of 9, co-authored 31 publications receiving 867 citations. Previous affiliations of Claudio Martani include École Polytechnique Fédérale de Lausanne & University of Cambridge.

Papers
More filters
Book ChapterDOI
26 Feb 2021
TL;DR: In this paper, the authors proposed a methodology to determine of optimal intervention strategies taking into consideration both the effects of sudden changes in environmental conditions and the effect of gradual deterioration processes, and the Monte Carlo method is used to simulate bridge behavior over time.
Abstract: Determining the intervention strategies for bridges should consider all possible ways that bridges can evolve over time. This means all possible failures at all possible times should be considered as well as how the infrastructure will be restored, and the effect of the restoration interventions on future behavior of the infrastructure. Infrastructure failures include those that occur due to gradual processes, e.g. the chloride induced corrosion that leads to an expansive rust product in a concrete bridge, and those that occur due to sudden failure processes, e.g. the washing away of a bridge due to high flood waters. The former occurs in much literature that is focused on the determination of optimal interventions strategies. The latter is normally dealt with under the guise of risk analysis. From a bridge management perspective, the former is acceptable when the probability of failure due to sudden processes is negligible, and the latter is acceptable when the probability of failure is so high so that interventions that might be required due to gradual processes can be neglected. This, however, still leaves a large number of possibilities where both should be considered. Recent research has shown that it is possible to determine optimal intervention strategies, taking into consideration both gradual deterioration processes and sudden changes in environmental conditions, at a high level of abstraction. A high level of abstraction is normally, however, something that might be satisfactory for making high level budget estimates but is lacking when it comes to estimating the specific interventions that should be executed on a bridge. With this in mind, this paper proposes a methodology to determine of optimal intervention strategies taking into consideration both the effects of sudden changes in environmental conditions and the effects of gradual deterioration processes. At this scope, fault trees are used to estimate the probability and impact of failures in each unit of time taking into consideration the condition of the objects, and the Monte Carlo method is used to simulate bridge behavior over time.

1 citations

DOI
01 Dec 2020
TL;DR: In this work the real options process is used to rigorously determine the best design for the new clinic of nuclear medicine of the university hospital of Zurich, suggesting that when some flexibility is embedded in the initial design, the estimated net benefit over the clinic’s lifetime is 167.18 million CHF.
Abstract: The uncertainty on the future treatments demand, recently evidenced by the COVID-19 pandemic, makes it challenging for hospitals managers to determine the optimal design of new clinics. Flexibility can help in optimally minimizing the service risks when the benefits of the investments justify the costs, considering the dynamism of treatment demand. In this work the real options process is used to rigorously determine the best design for the new clinic of nuclear medicine of the university hospital of Zurich. The results suggest that when some flexibility is embedded in the initial design, the estimated net benefit over the clinic’s lifetime is 167.18 million. CHF, which is 2.2% and 20% higher than the other two fix designs considered. Conclusions are then drawn on the advantages and limitations in using the real option process to optimize the design of a new hospital clinic, and suggestions are outlined for the further development of its use in practice.

1 citations

Journal ArticleDOI
25 Aug 2020
TL;DR: A new dynamic risk management methodology is proposed to consistently model the service, estimate the risk, first statically, using fault tree analysis, and then dynamically, using sensing technologies for data gathering and data-driven models for dynamic probability estimate, and finally implement the required intervention measures to minimize the risk.
Abstract: For an effective risk management of complex buildings it is required to dynamically estimate the risk on the service and take proper responsive measures to contrast it. This implies being able to estimate the evolving probabilities of failures over time and the way their occurrence is trust in affecting the service. This is now possible thanks to the advent of new sensing technologies and data-driven models to estimate failure probabilities, as well as solid risk management methodologies to estimate their effect on the service. However, it needs to be considered that the implementation of a dynamic risk management in standard building operation has to consider the reconfiguration of some processes to include the use of enabling technologies. In this paper a new dynamic risk management methodology is proposed to consistently (i) model the service, estimate the risk, first (ii) statically, using fault tree analysis, and then (iii) dynamically, using sensing technologies for data gathering and data-driven models for dynamic probability estimate, and finally (iv) implement the required intervention measures to minimize the risk. Then an application of the methodology is presented, for the risk management of an air handling unit, using a convolutional neural network, and its outcomes discussed. Conclusions are also drawn on the implications of integrating such a methodology in the current whole building risk management process and several outlooks are proposed.

Cited by
More filters
Journal ArticleDOI
TL;DR: This review highlights the research aimed at the implementation of MOFs as an integral part of solid-state microelectronics and discusses the fundamental and applied aspects of this two-pronged approach.
Abstract: Metal-organic frameworks (MOFs) are typically highlighted for their potential application in gas storage, separations and catalysis. In contrast, the unique prospects these porous and crystalline materials offer for application in electronic devices, although actively developed, are often underexposed. This review highlights the research aimed at the implementation of MOFs as an integral part of solid-state microelectronics. Manufacturing these devices will critically depend on the compatibility of MOFs with existing fabrication protocols and predominant standards. Therefore, it is important to focus in parallel on a fundamental understanding of the distinguishing properties of MOFs and eliminating fabrication-related obstacles for integration. The latter implies a shift from the microcrystalline powder synthesis in chemistry labs, towards film deposition and processing in a cleanroom environment. Both the fundamental and applied aspects of this two-pronged approach are discussed. Critical directions for future research are proposed in an updated high-level roadmap to stimulate the next steps towards MOF-based microelectronics within the community.

908 citations

Journal ArticleDOI
TL;DR: An exhaustive evaluation of 24 identical units of a commercial low-cost sensor platform against CEN (European Standardization Organization) reference analyzers, evaluating their measurement capability over time and a range of environmental conditions shows that their performance varies spatially and temporally.

607 citations

01 Jan 2010
TL;DR: In this article, the authors present the design and implementation of a presence sensor platform that can be used for accurate occupancy detection at the level of individual offices, which is low-cost, wireless, and incrementally deployable within existing buildings.
Abstract: Buildings are among the largest consumers of electricity in the US. A significant portion of this energy use in buildings can be attributed to HVAC systems used to maintain comfort for occupants. In most cases these building HVAC systems run on fixed schedules and do not employ any fine grained control based on detailed occupancy information. In this paper we present the design and implementation of a presence sensor platform that can be used for accurate occupancy detection at the level of individual offices. Our presence sensor is low-cost, wireless, and incrementally deployable within existing buildings. Using a pilot deployment of our system across ten offices over a two week period we identify significant opportunities for energy savings due to periods of vacancy. Our energy measurements show that our presence node has an estimated battery lifetime of over five years, while detecting occupancy accurately. Furthermore, using a building simulation framework and the occupancy information from our testbed, we show potential energy savings from 10% to 15% using our system.

489 citations

Journal ArticleDOI
TL;DR: Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment, and it can be argued that with a significant future expansion of monitoring networks, including indoor environments, there may be less need for wearable or portable sensors/monitors to assess personal exposure.

418 citations