Rigid impacts of three-dimensional rocking structures

Studies of rocking motion aim to explain the remarkable earthquake resistance of rocking structures. State-of-the-art assessment methods are mostly based on planar models, despite ongoing efforts to understand the significance of three-dimensionality. Impacts are essential components of rocking motion. We present experimental measurements of free-rocking blocks on a rigid surface, focusing on extreme sensitivity of impacts to geometric imperfections, unpredictability, and the emergence of three-dimensional motion via spontaneous symmetry breaking. These results inspire the development of new impact models of three-dimensional facet and edge impacts of polyhedral objects. Our model is a natural generalization of existing planar models based on the seminal work of George W. Housner. Model parameters are estimated empirically for rectangular blocks. Finally, new perspectives in earthquake assessment of rocking structures are discussed.

Development of a mathematical model of functioning system communications spacecraft

The paper discusses a mathematical model of the functioning of communication spacecraft, using systems of differential equations for translational and rotational motion, as well as the process of distributing problems in a constellation of three satellites. The model is implemented by means of the python 3.6 language and the computational method library numpy1.19. A series of computational experiments was carried out in order to estimate the energy costs for the operation of grouping with various orbital parameters and external impact models. The presented results of the experiments suggest the possibility of increasing the life of spacecraft by improving the operating system.

Evaluating the policy of closing bars and restaurants in Cataluña and its effects on mobility and COVID19 incidence

ABSTRACTThe world has gone through unprecedented changes since the global pandemic hit. During the early phase of the pandemic, the absence of known drugs or pharmaceutical treatments forced governments to introduce different policies in order to help reduce contagion rates and manage the economic consequences of the pandemic. This paper analyses the causal impact on mobility and COVID19 incidence from policy makers in Cataluña, Spain. We use annonimized phone-based mobility data together with reported incidence and apply a series of causal impact models frequently used in econometrics and policy evaluation in order to measure the policies impact.. We analyse the case of Cataluña and the public policy decision of closing all bars and restaurants down for a 5 week period between the 2020-16-10 to 2020-23-11. We find that this decision led to a significant reduction in mobility. It not only led to reductions in mobility but from a behavioural economics standpoint we highlight how people responded to the policy decision. Moreover, the policy of closing bars and restaurants slowed the incidence rate of COVID19 after a time lag has been taken into account. These finding are significant since governments worldwide want to restrict movements of people in order to slow down COVID19 incidence without infringing on their rights directly.

HEALTHY WORKING ENVIRONMENT, ORGANIZATION'S REPUTATION AND THEIR ‎IMPACT ON ‎EMPLOYEE'S ORGANIZATIONAL FIT: AN EXPLORATORY RESEARCH AT ‎SOME PRIVATE BANKS IN ‎BAGHDAD

The research aims to identify impact models of a healthy working environment ‎and the ‎organization's reputation on the employee's organizational fit. The ‎research population is ‎all private banks in Baghdad, a sample of six banks was ‎selected. 200 questionnaires ‎were distributed, 158 of them returned, 141 of them ‎were valid for analysis. The research ‎employed three approaches: Historical, ‎descriptive, and analytical. To clarify the research's ‎concepts, the first approach ‎was adopted, to clarify the dimensions of the research, the ‎second approach was ‎adopted, and to analyzing the research's dimensions the analytical ‎approach was ‎used. The Amos, 21 software was used to assess the validity of the study ‎model, ‎and the data were analyzed using the spss, 23 programs. The study came up ‎with ‎many conclusions, the most noteworthy of which was that: At the overall and ‎sub-level, the ‎healthy working environment has a statistically significant impact ‎on the employee's ‎organizational fit. And the organization's reputation plays a role ‎in the employee's ‎organizational fit, the impact models between the two ‎dimensions at the overall and sub-‎level were significant and statistical. The ‎research produced a series of recommendations ‎based on these findings, ‎intending to put their findings into reality‎.‎

Influence of the Characteristics of Weather Information in a Thunderstorm-Related Power Outage Prediction System

Thunderstorms are one of the most damaging weather phenomena in the United States, but they are also one of the least predictable. This unpredictable nature can make it especially challenging for emergency responders, infrastructure managers, and power utilities to be able to prepare and react to these types of events when they occur. Predictive analytical methods could be used to help power utilities adapt to these types of storms, but there are uncertainties inherent in the predictability of convective storms that pose a challenge to the accurate prediction of storm-related outages. Describing the strength and localized effects of thunderstorms remains a major technical challenge for meteorologists and weather modelers, and any predictive system for storm impacts will be limited by the quality of the data used to create it. We investigate how the quality of thunderstorm simulations affects power outage models by conducting a comparative analysis, using two different numerical weather prediction systems with different levels of data assimilation. We find that limitations in the weather simulations propagate into the outage model in specific and quantifiable ways, which has implications on how convective storms should be represented to these types of data-driven impact models in the future.

Globally consistent assessment of economic impacts of wildfires in CLIMADA v2.2

In light of the dramatic increase in economic impacts due to wildfires over recent years, the need for globally consistent impact modelling of wildfire damages is ever increasing. Insurance companies, individual households, humanitarian organisations and governmental authorities, as well as investors and portfolio owners, are increasingly required to account for climate-related physical risks. In this study we present a globally consistent and spatially explicit approach to modelling wildfire impacts using the open-source and open-access risk modelling platform CLIMADA (CLImate ADAptation). All input data is free, public and globally available, ensuring applicability in data-scarce regions of the Global South. The model was calibrated at resolutions of 1, 4 and 10 kilometers using information on past wildfire damage reported by the disaster database EM-DAT. Despite the large remaining uncertainties, the model yields sound damage estimates with a model performance well in line with the results of other natural catastrophe impact models, such as for tropical cyclones. To complement the global 10 perspective of this study, we conducted two case studies on the recent mega fires in Chile (2017) and Australia (2020). The model is made available online as part of a Python package, ready for application in practical contexts such as disaster risk assessment or physical climate risk disclosure.

Hard versus soft impact modeling of vibro-impact systems with a moving base

Soft and hard impact models applied to modeling of vibro-impact systems with a moving base are discussed. The conditions under which two collision models are equivalent in terms of equal energy dissipation are derived. These conditions differ from those presented in the literature. It is shown that in the case of a stiff, harmonically moving base with a low rate of energy dissipation, both methods yield the same results, but an application of the soft impact model to either the base with low stiffness or even the stiff base with a high rate of energy dissipation leads to different results from the ones for the hard impact model.

A comparative life cycle analysis of electromicrobial production systems

Electromicrobial production (EMP) processes represent an attractive strategy for the capture and conversion of CO2 into carbon-based products. We describe the development and application of comprehensive reactor, process, and life cycle impact models to analyze three major EMP systems relying on formate, H2, and acetate as intermediate molecules. Our results demonstrate that EMP systems can achieve a smaller carbon footprint than traditional bioprocessing strategies provided the electric grid is composed of >~90% renewable energy sources. For each of the three products we consider (biomass, enzymes, and lactic acid), the H2-mediated Knallgas bacteria system achieves the lowest overall global warming potential, indicating that this EMP strategy may be best-suited for industrial efforts based on current technology. We also identify environmental hotspots and process limitations that are key sites for future engineering and research efforts for each EMP system. Our analysis demonstrates the utility of an integrated bioelectrochemical model/life cycle assessment framework in both analyzing and aiding the ecodesign of electromicrobial processes and should help guide the design of working, scalable, and sustainable systems.

Experiences with virtual schools on “Climate data for impact assessments”

<p>The provision of climate services to users is a fast developing field. In support of this development, the IS-ENES3 project, funded within the EC Horizon2020 program, organized three schools on “Climate data for impact assessments” in 2020 and 2021. In an Autumn school, a Spring school and a Summer school, climate scientists and impact scientists were brought together. An important aim of the schools was to enhance interaction between Vulnerability-Impact-Adaptation (VIA) researchers, climate services providers and climate researchers. Another aim was to provide an overview of information on climate modeling, climate data, impact modelling and climate services based on the work of the IS-ENE3 project.</p><p>In the first three weeks a series of lectures was given, covering topics such as climate data and modelling, impact models, portals for accessing and processing climate data, setting-up impact assessments, and communication of results to stakeholders. In the last three weeks the participants worked in small groups of one climate scientist with one impact scientist on a case study under the guidance of the course lecturers. Impact and climate researchers were combined on purpose to let them experience how they could help each other.</p><p>Originally the schools were planned to take place on-site (e.g. in Prague) during one week; however, due to COVID-19 the schools had to be transformed to virtual schools with two weekly sessions during six weeks. Although the virtual set-up had some disadvantages (e.g. less possibilities for networking), there were also some advantages (e.g. the possibility to record the lectures and make them available to a broader audience; more time to explore and work with climate data in between the sessions, no CO<sub>2</sub> emissions for travelling). During this presentation we will present the set-up of the schools and the conversion to a virtual school. We will focus on the lessons learnt and the evaluation of the virtual schools by the participants and give some recommendations for similar schools and how to link the climate and VIA research communities .</p>