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Nexus of thermal resilience and energy efficiency in buildings: A case study of a nursing home
Extreme weather events become more frequent and severe due to climate change. Although energy efficiency technologies can influence thermal resilience of buildings, they are traditionally studied separately, and their interconnections are rarely quantified. This study developed a methodology of modeling and analysis to provide insights into the nexus of thermal resilience and energy efficiency of buildings. We conducted a case study of a real nursing home in Florida, where 12 patients died during Hurricane Irma in 2017 due to HVAC system power loss, to understand and quantify how passive and active energy efficiency measures (EEMs) can improve thermal resilience to reduce heat-exposure risk of patients. Results show that passive measures of opening windows and doors for natural ventilation, as well as miscellaneous load reduction, are very effective in eliminating the extreme dangerous occasions. However, to maintain safe conditions, active measures such as on-site power generators and thermal storage are also needed. The nursing home was further studied by changing its location to two other cities: San Francisco (mild climate) and Chicago (cold winter and hot summer). Results revealed that the EEMs' impacts on thermal resilience vary significantly by climate and building characteristics. The study also estimated the costs of EEMs to help stakeholders prioritize the measures. Passive measures that may not save energy may greatly improve thermal resilience, and thus should be considered in building design or retrofit. Findings from this study indicate energy efficiency technologies should be evaluated not only by their energy savings performance but also by their influence on a building's resilience to extreme weather events
A Pattern Language for High-Performance Computing Resilience
High-performance computing systems (HPC) provide powerful capabilities for
modeling, simulation, and data analytics for a broad class of computational
problems. They enable extreme performance of the order of quadrillion
floating-point arithmetic calculations per second by aggregating the power of
millions of compute, memory, networking and storage components. With the
rapidly growing scale and complexity of HPC systems for achieving even greater
performance, ensuring their reliable operation in the face of system
degradations and failures is a critical challenge. System fault events often
lead the scientific applications to produce incorrect results, or may even
cause their untimely termination. The sheer number of components in modern
extreme-scale HPC systems and the complex interactions and dependencies among
the hardware and software components, the applications, and the physical
environment makes the design of practical solutions that support fault
resilience a complex undertaking. To manage this complexity, we developed a
methodology for designing HPC resilience solutions using design patterns. We
codified the well-known techniques for handling faults, errors and failures
that have been devised, applied and improved upon over the past three decades
in the form of design patterns. In this paper, we present a pattern language to
enable a structured approach to the development of HPC resilience solutions.
The pattern language reveals the relations among the resilience patterns and
provides the means to explore alternative techniques for handling a specific
fault model that may have different efficiency and complexity characteristics.
Using the pattern language enables the design and implementation of
comprehensive resilience solutions as a set of interconnected resilience
patterns that can be instantiated across layers of the system stack.Comment: Proceedings of the 22nd European Conference on Pattern Languages of
Program
Extension and calibration of a Hawkes-based optimal execution model
We provide some theoretical extensions and a calibration protocol for our
former dynamic optimal execution model. The Hawkes parameters and the
propagator are estimated independently on financial data from stocks of the
CAC40. Interestingly, the propagator exhibits a smoothly decaying form with one
or two dominant time scales, but only so after a few seconds that the market
needs to adjust after a large trade. Motivated by our estimation results, we
derive the optimal execution strategy for a multi-exponential Hawkes kernel and
backtest it on the data for round trips. We find that the strategy is
profitable on average when trading at the midprice, which is in accordance with
violated martingale conditions. However, in most cases, these profits vanish
when we take bid-ask costs into account
Evaluating Cascading Impact of Attacks on Resilience of Industrial Control Systems: A Design-Centric Modeling Approach
A design-centric modeling approach was proposed to model the behaviour of the
physical processes controlled by Industrial Control Systems (ICS) and study the
cascading impact of data-oriented attacks. A threat model was used as input to
guide the construction of the CPS model where control components which are
within the adversary's intent and capabilities are extracted. The relevant
control components are subsequently modeled together with their control
dependencies and operational design specifications. The approach was
demonstrated and validated on a water treatment testbed. Attacks were simulated
on the testbed model where its resilience to attacks was evaluated using
proposed metrics such as Impact Ratio and Time-to-Critical-State. From the
analysis of the attacks, design strengths and weaknesses were identified and
design improvements were recommended to increase the testbed's resilience to
attacks
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