Miljko Bobrek

Johnson noise thermometry for harsh environments

The technology of temperature measurement appears to some to be a mature field. However, to many, requirements for improved performance and reliability are a driver for continual scientific and technology advancement. Although Johnson noise has been proposed as a thermometry method for several decades, it is only recently that digital and analog electronics have made it possible to economically fabricate measurement systems based on Johnson noise. Johnson noise, which is a result of fundamental physics, is caused by the random thermal motions of electrons in all conductors. Its fundamental nature allows us to construct temperature measurement systems that do not require periodic calibration. Thus long, unattended operating intervals are feasible. Several unique implementations of Johnson noise thermometry (JNT) are possible. One permits temperature measurement without contacting the measured surface nductive JNT. Another implementation measures the Johnson noise of a resistance element in contact with the measured surface - conductive JNT. The resistive element in conductive JNT can be an RTD. Apparatus have been recently fabricated demonstrating the practicality of both JNT implementations. A demonstration of conductive JNT is planned at a nuclear facility within two years. We present new hardware implementations that allow real-time calibration of the signals that have the potential of allowing a fully-integrated, physically small and robust system to be achieved.

Building energy management using learning-from-signals

ORNL recently applied its “learning-from-signals” (LFS) techniques to evaluating and improving the energy efficiency of buildings at military installations. LFS is a term coined by ORNL to describe the machine learning algorithms that it has developed for mining, processing, and classifying signals either purposefully or inadvertently being picked up from infrastructure or individual devices. For this particular application, ORNL provided technical support to the Defense Advanced Research Projects Agency (DARPA) Service Chiefs Program for disaggregating electrical power consumption at the device level in a military residential dormitory at Fort Meyer in Washington, DC. The ORNL researchers showed that patterns of device utilization could be monitored on a buildings power infrastructure. These devices included cooling/heating water pumps, lighting, washers, dryers, refrigerators, and stoves. This paper discusses the process and initial results of the research effort, as well as the path forward for similar industrial, commercial, and government undertakings.

Real-time urban population monitoring using pervasive sensor network

It is estimated that 50% of the global population lives in urban areas occupying just 0.4% of the Earths surface. Understanding urban activity constitutes monitoring population density and its changes over time, in urban environments. Currently, there are limited mechanisms to non-intrusively monitor population density in real-time. The pervasive use of cellular phones in urban areas is one such mechanism that provides a unique opportunity to study population density by monitoring the mobility patterns in near real-time. Cellular carriers such as AT&T harvest such data through their cell towers; however, this data is proprietary and the carriers restrict access, due to privacy concerns. In this work, we propose a system that passively senses the population density and infers mobility patterns in an urban area by monitoring power spectral density in cellular frequency bands using periodic beacons from each cellphone without knowing who and where they are located. A wireless sensor network platform is being developed to perform spectral monitoring along with environmental measurements. Algorithms are developed to generate real-time fine-resolution population estimates.

Radiation-Hardened Circuitry Using Mask-Programmable Analog Arrays. Final Report

As the recent accident at Fukushima Daiichi so vividly demonstrated, telerobotic technologies capable of withstanding high radiation environments need to be readily available to enable operations, repair, and recovery under severe accident scenarios where human entry is extremely dangerous or not possible. Telerobotic technologies that enable remote operation in high dose rate environments have undergone revolutionary improvement over the past few decades. However, much of this technology cannot be employed in nuclear power environments due the radiation sensitivity of the electronics and the organic insulator materials currently in use. This is the final report of the activities involving the NEET 2 project Radiation Hardened Circuitry Using Mask-Programmable Analog Arrays. We present a detailed functional block diagram of the proposed data acquisition system, the thought process leading to technical decisions, the implemented system, and the tested results from the systems. This system will be capable of monitoring at least three parameters of importance to nuclear reactor monitoring: temperature, radiation level, and pressure.

An integrated signaling-encryption mechanism to reduce error propagation in wireless communications: performance analyses

Traditional encryption techniques require packet overhead, produce processing time delay, and suffer from severe quality of service deterioration due to fades and interference in wireless channels. These issues reduce the effective transmission data rate (throughput) considerably in wireless communications, where data rate with limited bandwidth is the main constraint. In this paper, performance evaluation analyses are conducted for an integrated signaling-encryption mechanism that is secure and enables improved throughput and probability of bit-error in wireless channels. This mechanism eliminates the drawbacks stated herein by encrypting only a small portion of an entire transmitted frame, while the rest is not subject to traditional encryption but goes through a signaling process (designed transformation) with the plaintext of the portion selected for encryption. We also propose to incorporate error correction coding solely on the small encrypted portion of the data to drastically improve the overall bit-error rate performance while not noticeably increasing the required bit-rate. We focus on validating the signaling-encryption mechanism utilizing Hamming and convolutional error correction coding by conducting an end-to-end system-level simulation-based study. The average probability of bit-error and throughput of the encryption mechanism are evaluated over standard Gaussian and Rayleigh fading-type channels and compared to the ones of the conventional advanced encryption standard (AES).