Everything about Probabilistic design
Discipline within engineering design
Probabilistic design is a discipline within engineering design. It deals primarily with the consideration and minimization of the effects of random variability upon the performance of an engineering system during the design phase. Typically, these effects studied and optimized are related to quality and reliability. It differs from the classical approach to design by assuming a small probability of failure instead of using the safety factor. Probabilistic design is used in a variety of different applications to assess the likelihood of failure. Disciplines which extensively use probabilistic design principles include product design, quality control, systems engineering, machine design, civil engineering and manufacturing. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Probabilistic designA 5-minute orientation
- Skim a recent paper: Interpretable Memristive LSTM Network Design for Probabilistic Residential Load ForecastingInfluential work since 2022
- Pick up a classic book: Analytic & Probabilistic Methods in Number TheoryThe most-reprinted book on the subject
- Read the landmark paper: Probabilistic design of slopesCited 265 times
- Go sideways: Doob's martingale convergence theoremsA closely related topic
- Go sideways: Line samplingA closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Probabilistic design of slopes
Towards fully probabilistic control design
Probabilistic Design of Wind Turbines
Developments towards full probabilistic design codes
Three-Dimensional, Probabilistic Highway Design
Should Probabilistic Design Replace Safety Factors?
Fully probabilistic control design
Axiomatisation of fully probabilistic design
🆕 Influential since 2022
Interpretable Memristive LSTM Network Design for Probabilistic Residential Load Forecasting
Probabilistic Digital Twin for Additive Manufacturing Process Design and Control
A Joint Communication and Computation Design for Probabilistic Semantic Communications
Probabilistic selection and design of concrete using machine learning
Probabilistic product design with regret-anticipated consumers
đź“š Books worth reading
Analytic & Probabilistic Methods in Number TheoryRanked by number of editions on Open Library, a rough measure of how lasting a book is.
đź”— Related topics
- Doob's martingale convergence theorems In mathematics – specifically, in the theory of stochastic processes – Doob's martingale convergence theorems are a collection of results on the limits…
- Line sampling Line sampling is a method used in reliability engineering to compute small (i.e., rare event) failure probabilities encountered in engineering systems…
- Probability bounds analysis Probability bounds analysis (PBA) is a collection of methods of uncertainty propagation for making qualitative and quantitative calculations in the face…
- Doob–Dynkin lemma In probability theory, the Doob–Dynkin lemma, named after Joseph L. Doob and Eugene Dynkin (also known as the factorization lemma), characterizes the situation…
- Uncertainty quantification Uncertainty Quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world application…
- Standard probability space In probability theory, a standard probability space, also called Lebesgue–Rokhlin probability space or just Lebesgue space (the latter term is ambiguous)…
- Martingale (probability theory) In probability theory, a martingale is a stochastic process in which the expected value of the next observation, given all prior observations, is equal…
- Random element In probability theory, random element is a generalization of the concept of random variable to more complicated spaces than the simple real line. The concept…