Context. One of the long-term goals of exoplanet science is the atmospheric characterization of dozens of small exoplanets in order to understand their diversity and search for habitable worlds and potential biosignatures. Achieving this goal requires a space mission of sufficient scale that can spatially separate the signals from exoplanets and their host stars and thus directly scrutinize the exoplanets and their atmospheres. Aims. We seek to quantify the exoplanet detection performance of a space-based mid-infrared (MIR) nulling interferometer that measures the thermal emission of exoplanets. We study the impact of various parameters and compare the performance with that of large single-aperture mission concepts that detect exoplanets in reflected light. Methods. We have developed an instrument simulator that considers all major astrophysical noise sources and coupled it with Monte Carlo simulations of a synthetic exoplanet population around main-sequence stars within 20 pc of the Sun. This allows us to quantify the number (and types) of exoplanets that our mission concept could detect. Considering single visits only, we discuss two different scenarios for distributing 2.5 yr of an initial search phase among the stellar targets. Different apertures sizes and wavelength ranges are investigated. Results. An interferometer consisting of four 2 m apertures working in the 4–18.5 μ.m wavelength range with a total instrument throughput of 5% could detect up to ≈550 exoplanets with radii between 0.5 and 6 R⊕ with an integrated S/N ≥ 7. At least ≈160 of the detected exoplanets have radii ≤1.5 R⊕. Depending on the observing scenario, ≈25–45 rocky exoplanets (objects with radii between 0.5 and 1.5 R⊕) orbiting within the empirical habitable zone (eHZ) of their host stars are among the detections. With four 3.5 m apertures, the total number of detections can increase to up to ≈770, including ≈60–80 rocky eHZ planets. With four times 1 m apertures, the maximum detection yield is ≈315 exoplanets, including ≤20 rocky eHZ planets. The vast majority of small, temperate exoplanets are detected around M dwarfs. The impact of changing the wavelength range to 3–20 μm or 6–17 μm on the detection yield is negligible. Conclusions. A large space-based MIR nulling interferometer will be able to directly detect hundreds of small, nearby exoplanets, tens of which would be habitable world candidates. This shows that such a mission can compete with large single-aperture reflected light missions. Further increasing the number of habitable world candidates, in particular around solar-type stars, appears possible via the implementation of a multi-visit strategy during the search phase. The high median S/N of most of the detected planets will allow for first estimates of their radii and effective temperatures and will help prioritize the targets for a second mission phase to obtain high-S/N thermal emission spectra, leveraging the superior diagnostic power of the MIR regime compared to shorter wavelengths.

Context. The Large Interferometer For Exoplanets (LIFE) initiative is developing the science and a technology road map for an ambitious space mission featuring a space-based mid-infrared (MIR) nulling interferometer in order to detect the thermal emission of hundreds of exoplanets and characterize their atmospheres. Aims. In order to quantify the science potential of such a mission, in particular in the context of technical trade-offs, an instrument simulator is required. In addition, signal extraction algorithms are needed to verify that exoplanet properties (e.g., angular separation and spectral flux) contained in simulated exoplanet data sets can be accurately retrieved. Methods. We present LIFEsim, a software tool developed for simulating observations of exoplanetary systems with an MIR space-based nulling interferometer. It includes astrophysical noise sources (i.e., stellar leakage and thermal emission from local zodiacal and exozodiacal dust) and offers the flexibility to include instrumental noise terms in the future. Here, we provide some first quantitative limits on instrumental effects that would allow the measurements to remain in the fundamental noise limited regime. We demonstrate updated signal extraction approaches to validating signal-to-noise ratio (S/N) estimates from the simulator. Monte Carlo simulations are used to generate a mock survey of nearby terrestrial exoplanets and determine to which accuracy fundamental planet properties can be retrieved. Results. LIFEsim provides an accessible way to predict the expected S/N of future observations as a function of various key instrument and target parameters. The S/Ns of the extracted spectra are photon noise dominated, as expected from our current simulations. Signals from multi-planet systems can be reliably extracted. From single-epoch observations in our mock survey of small (R < 1.5 REarth) planets orbiting within the habitable zones of their stars, we find that typical uncertainties in the estimated effective temperature of the exoplanets are ≲10%, for the exoplanet radius ≲20%, and for the separation from the host star ≲2%. Signal-to-noise-ratio values obtained in the signal extraction process deviate by less than 10% from purely photon-counting statistics-based S/Ns. Conclusions. LIFEsim has been sufficiently well validated so that it can be shared with a broader community interested in quantifying various exoplanet science cases that a future space-based MIR nulling interferometer could address. Reliable signal extraction algorithms exist, and our results underline the power of the MIR wavelength range for deriving fundamental exoplanet properties from single-epoch observations.

In order to overcome negative consequences of a disaster, buildings and infrastructures need to be resilient. After a disaster occurs, they must get back to their normal operations as quickly as possible. Buildings and infrastructures should incorporate both pre-event (preparedness and mitigation) and post-event (response and recovery) resilience activities to minimize negative effects of a disaster. Quantitative approaches for measuring resilience for buildings and infrastructures need to be developed. A proposed methodology for quantification of resilience of a given building type based on different hurricane categories is presented. The formulation for the resilience quantification is based on a model embedding several distinct parameters (for example, structural loss ratios, conditional probabilities of exceeding for damage states, estimated and actual recovery times, wind speed probability). The proposed resilience formulation is applied to a residential building type selected from HAZUS. Numerical results of resilience for the selected residential building type against Category 1, 2, and 3 hurricanes are presented in a dashboard representation. Resilience performance indicators between different types of buildings, which are identical except for their roof types, have been evaluated in order to present applicability of the proposed methodology.

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The twenty-first century is defined by the social and technical hazards we face. A hazardous situation is a condition, or event, that threatens the well-being of people, organizations, societies, environments, and property. The most extreme of the hazards are considered X-Events and are an exogenous source of extreme stress to a system. X-Events can also be the unintended outputs of a system with both positive (serendipitous) and negative (catastrophic) consequences. Systems can vary in their ability to withstand these stress events. This ability exists on a continuum of fragility that ranges from fragile (degrading with stress), to robust (unchanged by stress), to antifragile (improving with stress). The state of the art does not include a method for analyzing or measuring fragility. Given that "what we measure we will improve," the absence of a measurement approach limits the effectiveness of governance in making our systems less fragile and more robust if not antifragile. The authors present an antifragile system simulation model, and propose a framework for analyzing and measuring antifragility based on system of systems concepts. The framework reduces a multidimensional concept of fragility into a two-dimensional continuous interval scale.

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