State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science

Comment on "Time-Dependent Density-Matrix Renormalization Group: A Systematic Method for the Study of Quantum Many-Body Out-of- Equilibrium Systems"

In a recent Letter [Phys. Rev. Lett. 88, 256403(2002), cond-mat/0109158] Cazalilla and Marston proposed a time-dependent density- matrix renormalization group (TdDMRG) algorithm for the accurate evaluation of out-of-equilibrium properties of quantum many-body systems. For a point contact junction between two Luttinger liquids, a current oscillation develops after initial transient in the insulating regime. Here we would like to point out that (a) the observed oscillation is an artifact of the method; (b) the TdDMRG can be significantly improved by incorporating the non-equilibrium evolution of the goundstate into the density matrix.Comment: 1 page, 2 figure

Improved lattice QCD with quarks: the 2 dimensional case

QCD in two dimensions is investigated using the improved fermionic lattice Hamiltonian proposed by Luo, Chen, Xu, and Jiang. We show that the improved theory leads to a significant reduction of the finite lattice spacing errors. The quark condensate and the mass of lightest quark and anti-quark bound state in the strong coupling phase (different from t'Hooft phase) are computed. We find agreement between our results and the analytical ones in the continuum.Comment: LaTeX file (including text + 10 figures

In-plane ferromagnetism in charge-ordering Na0.55CoO2Na_{0.55}CoO_2

The magnetic and transport properties are systematically studied on the single crystal $Na_{0.55}CoO_2$ with charge ordering and divergency in resistivity below 50 K. A long-range ferromagnetic ordering is observed in susceptibility below 20 K with the magnetic field parallel to Co-O plane, while a negligible behavior is observed with the field perpendicular to the Co-O plane. It definitely gives a direct evidence for the existence of in-plane ferromagnetism below 20 K. The observed magnetoresistance (MR) of 30 % at the field of 6 T at low temperatures indicates an unexpectedly strong spin-charge coupling in triangle lattice systems.Comment: 4 pages, 5 figure

Visualizing urban microclimate and quantifying its impact on building energy use in San Francisco

Weather data at nearby airports are usually used in building energy simulation to estimate energy use in buildings or evaluate building design or retrofit options. However, due to urbanization and geography characteristics, local weather conditions can differ significantly from those at airports. This study presents the visualization of 10-year hourly weather data measured at 27 sites in San Francisco, aiming to provide insights into the urban microclimate and urban heat island effect in San Francisco and how they evolve during the recent decade. The 10-year weather data are used in building energy simulations to investigate its influence on energy use and electrical peak demand, which informs the city's policy making on building energy efficiency and resilience. The visualization feature is implemented in CityBES, an open web-based data and computing platform for urban building energy research

Full Wave Form Inversion for Seismic Data

In seismic wave inversion, seismic waves are sent into the ground and then observed at many receiving points with the aim of producing high-resolution images of the geological underground details. The challenge presented by Saudi Aramco is to solve the inverse problem for multiple point sources on the full elastic wave equation, taking into account all frequencies for the best resolution. The state-of-the-art methods use optimisation to find the seismic properties of the rocks, such that when used as the coefficients of the equations of a model, the measurements are reproduced as closely as possible. This process requires regularisation if one is to avoid instability. The approach can produce a realistic image but does not account for uncertainty arising, in general, from the existence of many different patterns of properties that also reproduce the measurements. In the Study Group a formulation of the problem was developed, based upon the principles of Bayesian statistics. First the state-of-the-art optimisation method was shown to be a special case of the Bayesian formulation. This result immediately provides insight into the most appropriate regularisation methods. Then a practical implementation of a sequential sampling algorithm, using forms of the Ensemble Kalman Filter, was devised and explored

Novel dynamical effects and glassy response in strongly correlated electronic system

We find an unconventional nucleation of low temperature paramagnetic metal (PMM) phase with monoclinic structure from the matrix of high-temperature antiferromagnetic insulator (AFI) phase with tetragonal structure in strongly correlated electronic system $BaCo_{0.9}Ni_{0.1}S_{1.97}$. Such unconventional nucleation leads to a decease in resistivity by several orders with relaxation at a fixed temperature without external perturbation. The novel dynamical process could arise from the competition of strain fields, Coulomb interactions, magnetic correlations and disorders. Such competition may frustrate the nucleation, giving rise to a slow, nonexponential relaxation and "physical aging" behavior.Comment: 5 pages, 4 figure

Hysteresis and Anisotropic Magnetoresistance in Antiferromagnetic Nd2−xCexCuO4Nd_{2-x}Ce_xCuO_{4}

The out-of-plane resistivity ($\rho_c$) and magnetoresistivity (MR) are studied in antiferromangetic (AF) $Nd_{2-x}Ce_xCuO_{4}$ single crystals, which have three types of noncollinear antiferromangetic spin structures. The apparent signatures are observed in $\rho_c(T)$ measured at the zero-field and 14 T at the spin structure transitions, giving a definite evidence for the itinerant electrons directly coupled to the localized spins. One of striking feature is an anisotropy of the MR with a fourfold symmetry upon rotating the external field (B) within ab plane in the different phases, while twofold symmetry at spin reorientation transition temperatures. The intriguing thermal hysteresis in $\rho_c(T,B)$ and magnetic hysteresis in MR are observed at spin reorientation transition temperatures.Comment: 4 pages, 4 figure

Oxygen Isotope Effect on the Spin State Transition in (Pr0.7_{0.7}Sm0.3_{0.3})0.7_{0.7}Ca0.3_{0.3}CoO3{_3}

Oxygen isotope substitution is performed in the perovskite cobalt oxide (Pr$_{0.7}$Sm$_{0.3}$)$_{0.7}$Ca$_{0.3}$CoO${_3}$ which shows a sharp spin state transition from the intermediate spin (IS) state to the low spin (LS) state at a certain temperature. The transition temperature of the spin state up-shifts with the substitution of $^{16}O$ by $^{18}$O from the resistivity and magnetic susceptibility measurements. The up-shift value is 6.8 K and an oxygen isotope exponent ($\alpha_S$) is about -0.8. The large oxygen isotope effect indicates strong electron-phonon coupling in this material. The substitution of $^{16}$O by $^{18}$O leads to a decrease in the frequency of phonon and an increase in the effective mass of electron ($m$$^\ast$), so that the bandwidth W is decreased and the energy difference between the different spin states is increased. This is the reason why the $T_s$ is shifted to high temperature with oxygen isotopic exchange.Comment: 4 pages, 3 figure

Dimensional crossover and anomalous magnetoresistivity in single crystals NaxCoO2Na_xCoO_2

The in-plane ($\rho_{ab}$) and c-axis ($\rho_c$) resistivities, and the magnetoresistivity of single crystals $Na_xCoO_2$ with x = 0.7, 0.5 and 0.3 were studied systematically. $\rho_{ab}(T)$ shows similar temperature dependence between $Na_{0.3}CoO_2$ and $Na_{0.7}CoO_2$, while $\rho_c(T)$ is quite different. A dimensional crossover from two to three occurs with decreasing Na concentration from 0.7 to 0.3. The angular dependence of in-plane magnetoresistivity for 0.5 sample shows a \emph{"d-wave-like"} symmetry at 2K, while the \emph{"p-wave-like"} symmetry at 20 K. These results give an evidence for existence of a \emph{spin ordering orientation} below 20 K turned by external field, like the stripes in cuprates.Comment: 4 pages, 3 figure