Innovating physical products can be seen as systems engineering at a higher abstraction level. It spans multiple domains and focuses not on developing the product, but realising the complete innovation. In our new approach, we focus on the four most important domains of physical product innovation: market, technology, production and business. Technology Innovation Processes (TIP) is a newly developed, flexible and pragmatic data-informed decision approach that helps innovation managers to navigate through the early stages of a blue-ocean innovation process, where not much is known.
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We present a method for measuring gait velocity using data from an existing ambient sensor network. Gait velocity is an important predictor of fall risk and functional health. In contrast to other approaches that use specific sensors or sensor configurations our method imposes no constraints on the elderly. We studied different probabilistic models for the description of the sensor patterns. Experiments are carried out on 15 months of data and include repeated assessments from an occupational therapist. We showed that the measured gait velocities correlate with these assessments.
Precast concrete structures are preferred for facilities with large open areas due to easiness in construction. Such structures are typically composed of individual columns and long-span beams, and are quite flexible and of limited redundancy. In this paper, nonlinear dynamic analyses of a typical such structure are conducted using as excitation 54 ground motions recorded on top of a variety of soils (hard, soft, and liquefied soil sites). The results show that liquefaction-affected level-ground motions systematically impose a greater threat to precast-concrete structures in terms of seismic demand, even when low values of elastic spectral acceleration prevail, as opposed to soft-soil records and even more to hard-soil ones. Thus, elastic spectral acceleration appears to be an insufficient engineering demand parameter for design. Soil effects, the “signature” of which is born on ground motions, are first uncovered using wavelet analysis to detect the evolution of the energy and frequency content of the ground motion in the time domain. From this, the changes in effective (“dominant”) excitation period are noted, persuasively attributed to the nature of the soil, and finally correlated with the observed structural behavior.
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In the coming decades, a substantial number of electric vehicle (EV) chargers need to be installed. The Dutch Climate Accord, accordingly, urges for preparation of regional-scale spatial programs with focus on transport infrastructure for three major metropolitan regions among them Amsterdam Metropolitan Area (AMA). Spatial allocation of EV chargers could be approached at two different spatial scales. At the metropolitan scale, given the inter-regional flow of cars, the EV chargers of one neighbourhood could serve visitors from other neighbourhoods during days. At the neighbourhood scale, EV chargers need to be allocated as close as possible to electricity substations, and within a walkable distance from the final destination of EV drivers during days and nights, i.e. amenities, jobs, and dwellings. This study aims to bridge the gap in the previous studies, that is dealing with only of the two scales, by conducting a two-phase study on EV infrastructure. At the first phase of the study, the necessary number of new EV chargers in 353 4-digit postcodes of AMA will be calculated. On the basis of the findings of the Phase 1, as a case study, EV chargers will be allocated at the candidate street parking locations in the Amsterdam West borough. The methods of the study are Mixed-integer nonlinear programming, accessibility and street pattern analysis. The study will be conducted on the basis of data of regional scale travel behaviour survey and the location of dwellings, existing chargers, jobs, amenities, and electricity substations.
